Salient Feature Selection Using Feed-Forward Neural Networks and Signal-to-Noise Ratios with a Focus Toward Network Threat Detection and Risk Level identification

Most communication in the modern era takes place over some type of cyber network, to include telecommunications, banking, public utilities, and health systems. Information gained from illegitimate network access can be used to create catastrophic effects at the individual, corporate, national, and even international levels, making cyber security a top priority. Cyber networks frequently encounter amounts of network traffic too large to process real-time threat detection efficiently. Reducing the amount of information necessary for a network monitor to determine the presence of a threat would likely aide in keeping networks more secure. This thesis uses network traffic data captured during the Department of Defense Cyber Defense Exercise to determine which features of network traffic are salient to detecting and classifying threats. After generating a set of 248 features from the capture data, feed-forward artificial neural networks were generated and signal-to-noise ratios were used to prune the feature set to 18 features while still achieving an accuracy ranging from 83% - 94%. The salient features primarily come from the transport layer section of the network traffic data and involve the client/server connection parameters, size of the initial data sent, and number of segments and/or bytes sent in the flow

Comprehensive genomic characterization of five canine lymphoid tumor cell lines

Abstract Background Leukemia/lymphoma cell lines have been critical in the investigation of the pathogenesis and therapy of hematological malignancies. While human LL cell lines have generally been found to recapitulate the primary tumors from which they were derived, appropriate characterization including cytogenetic and transcriptional assessment is crucial for assessing their clinical predictive value. Results In the following study, five canine LL cell lines, CLBL-1, Ema, TL-1 (Nody-1), UL-1, and 3132, were characterized using extensive immunophenotyping, karyotypic analysis, oligonucleotide array comparative genomic hybridization (oaCGH), and gene expression profiling. Genome-wide DNA copy number data from the cell lines were also directly compared with 299 primary canine round cell tumors to determine whether the cell lines represent primary tumors, and, if so, what subtype each most closely resembled. Conclusions Based on integrated analyses, CLBL-1 was classified as B-cell lymphoma, Ema and TL-1 as T-cell lymphoma, and UL-1 as T-cell acute lymphoblastic leukemia. 3132, originally classified as a B-cell lymphoma, was reclassified as a histiocytic sarcoma based on characteristic cytogenomic properties. In combination, these data begin to elucidate the clinical predictive value of these cell lines which will enhance the appropriate selection of in vitro models for future studies of canine hematological malignancies

Aggressiveness of Phytophthora medicaginis on chickpea: Phenotyping method determines isolate ranking and host genotype-by-isolate interactions

Phytophthora medicaginis causing Phytophthora root rot of chickpea (Cicer arietinum) is an important disease, with genetic resistance using C. arietinum × Cicer echinospermum crosses as the main disease management strategy. We evaluated pathogenic variation in P. medicaginis populations with the aim of improving phenotyping methods for disease resistance. We addressed the question of individual isolate aggressiveness across four different seedling-based phenotyping methods conducted in glasshouses and one field-based phenotyping method. Our results revealed that a seedling media surface inoculation method used on a susceptible C. arietinum variety and a moderately resistant C. arietinum × C. echinospermum backcross detected the greatest variability in aggressiveness among 37 P. medicaginis isolates. Evaluations of different components of resistance, using our different phenotyping methods, revealed that differential pathogen–isolate reactions occur with some phenotyping methods. We found support for our hypotheses that the level of aggressiveness of P. medicaginis isolates depends on the phenotyping method, and that phenotyping methods interact with both isolate and host genotype reactions. Our cup-based root inoculation method showed promise as a non-field-based phenotyping method, as it provided significant correlations with genotype–isolate rankings in the field experiment for a number of disease parameters

Linking physical activity to breast cancer:text mining results and a protocol for systematically reviewing three potential mechanistic pathways

Epidemiological research suggests that physical activity is associated with a reduced risk of breast cancer, but the causal nature of this link is not clear. Investigating mechanistic pathways can provide evidence of biological plausibility and improve causal inference. This project will examine three putative pathways (sex steroid hormones, insulin signalling, and inflammation) in a series of two-stage systematic reviews. Stage 1 used Text Mining for Mechanism Prioritisation (TeMMPo) to identify and prioritise relevant biological intermediates. Stage 2 will systematically review the findings from studies of (i) physical activity and intermediates; and (ii) intermediates and breast cancer. Ovid MEDLINE, EMBASE, and SPORTDiscus will be searched using a combination of subject headings and free-text terms. Human intervention and prospective, observational studies will be eligible for inclusion. Meta-analysis will be performed where possible. Risk of bias will be assessed using the Cochrane Collaboration tool, the ROBINS-I or ROBINS-E tool, depending on study type. Strength of evidence will be assessed using the GRADE system. In addition to synthesising the mechanistic evidence that links physical activity with breast cancer risk, this project may also identify priority areas for future research and help inform the design and implementation of physical activity interventions

Linking Physical Activity to Breast Cancer via Sex Steroid Hormones, Part 2:The Effect of Sex Steroid Hormones on Breast Cancer Risk

We undertook a systematic review and appraised the evidence for an effect of circulating sex steroid hormones and sex hormone–binding globulin (SHBG) on breast cancer risk in pre- and postmenopausal women. Systematic searches identified prospective studies relevant to this review. Meta-analyses estimated breast cancer risk for women with the highest compared with the lowest level of sex hormones, and the DRMETA Stata package was used to graphically represent the shape of these associations. The ROBINS-E tool assessed risk of bias, and the GRADE system appraised the strength of evidence. In premenopausal women, there was little evidence that estrogens, progesterone, or SHBG were associated with breast cancer risk, whereas androgens showed a positive association. In postmenopausal women, higher estrogens and androgens were associated with an increase in breast cancer risk, whereas higher SHBG was inversely associated with risk. The strength of the evidence quality ranged from low to high for each hormone. Dose–response relationships between sex steroid hormone concentrations and breast cancer risk were most notable for post-menopausal women. These data support the plausibility of a role for sex steroid hormones in mediating the causal relationship between physical activity and the risk of breast cancer. See related reviews by Lynch et al., p. 11 and Swain et al., p. 1

Association of early HIV viremia with mortality after HIV-associated lymphoma

To examine the association between early HIV viremia and mortality after HIV-associated lymphoma

Lymphoma Immune Reconstitution Inflammatory Syndrome in the Center for AIDS Research Network of Integrated Clinical Systems Cohort

Background. Lymphoma incidence is increased among human immunodeficiency virus (HIV)–infected individuals soon after antiretroviral therapy (ART), perhaps due to unmasking immune reconstitution inflammatory syndrome (IRIS). Clinical characteristics and survival for unmasking lymphoma IRIS have not been described

Assessing the relationship of patient reported outcome measures with functional status in dysferlinopathy: a Rasch analysis approach

Dysferlinopathy is a muscular dystrophy with a highly variable functional disease progression in which the relationship of function to some patient reported outcome measures (PROMs) has not been previously reported. This analysis aims to identify the suitability of PROMs and their association with motor performance.Two-hundred and four patients with dysferlinopathy were identified in the Jain Foundation's Clinical Outcome Study in Dysferlinopathy from 14 sites in 8 countries. All patients completed the following PROMs: Individualized Neuromuscular Quality of Life Questionnaire (INQoL), International Physical Activity Questionnaire (IPAQ), and activity limitations for patients with upper and/or lower limb impairments (ACTIVLIMs). In addition, nonambulant patients completed the Egen Klassifikation Scale (EK). Assessments were conducted annually at baseline, years 1, 2, 3, and 4. Data were also collected on the North Star Assessment for Limb Girdle Type Muscular Dystrophies (NSAD) and Performance of Upper Limb (PUL) at these time points from year 2. Data were analyzed using descriptive statistics and Rasch analysis was conducted on ACTIVLIM, EK, INQoL. For associations, graphs (NSAD with ACTIVLIM, IPAQ and INQoL and EK with PUL) were generated from generalized estimating equations (GEE). The ACTIVLIM appeared robust psychometrically and was strongly associated with the NSAD total score (Pseudo R(2) 0.68). The INQoL performed less well and was poorly associated with the NSAD total score (Pseudo R(2) 0.18). EK scores were strongly associated with PUL (Pseudo R(2) 0.69). IPAQ was poorly associated with NSAD scores (Pseudo R(2) 0.09). This study showed that several of the chosen PROMs demonstrated change over time and a good association with functional outcomes. An alternative quality of life measure and method of collecting data on physical activity may need to be selected for assessing dysferlinopathy

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead