Two-step light gradient boosted model to identify human west nile virus infection risk factor in Chicago.

West Nile virus (WNV), a flavivirus transmitted by mosquito bites, causes primarily mild symptoms but can also be fatal. Therefore, predicting and controlling the spread of West Nile virus is essential for public health in endemic areas. We hypothesized that socioeconomic factors may influence human risk from WNV. We analyzed a list of weather, land use, mosquito surveillance, and socioeconomic variables for predicting WNV cases in 1-km hexagonal grids across the Chicago metropolitan area. We used a two-stage lightGBM approach to perform the analysis and found that hexagons with incomes above and below the median are influenced by the same top characteristics. We found that weather factors and mosquito infection rates were the strongest common factors. Land use and socioeconomic variables had relatively small contributions in predicting WNV cases. The Light GBM handles unbalanced data sets well and provides meaningful predictions of the risk of epidemic disease outbreaks.

Feature Pyramid U-Net with Attention for Semantic Segmentation of Forward-Looking Sonar Images.

Forward-looking sonar is a technique widely used for underwater detection. However, most sonar images have underwater noise and low resolution due to their acoustic properties. In recent years, the semantic segmentation model U-Net has shown excellent segmentation performance, and it has great potential in forward-looking sonar image segmentation. However, forward-looking sonar images are affected by noise, which prevents the existing U-Net model from segmenting small objects effectively. Therefore, this study presents a forward-looking sonar semantic segmentation model called Feature Pyramid U-Net with Attention (FPUA). This model uses residual blocks to improve the training depth of the network. To improve the segmentation accuracy of the network for small objects, a feature pyramid module combined with an attention structure is introduced. This improves the model's ability to learn deep semantic and shallow detail information. First, the proposed model is compared against other deep learning models and on two datasets, of which one was collected in a tank environment and the other was collected in a real marine environment. To further test the validity of the model, a real forward-looking sonar system was devised and employed in the lake trials. The results show that the proposed model performs better than the other models for small-object and few-sample classes and that it is competitive in semantic segmentation of forward-looking sonar images.

Apoptosis as an underlying mechanism in lymphocytes induced by riboflavin and ultraviolet light.

Riboflavin plus UV light pathogen reduction technology (RF-PRT) is an effective method for inactivating donor-derived leukocytes (DDLs) in blood components. Literature data have shown that reactive oxygen species (ROS) increased in lymphocytes after RF-PRT treatment. Sustained high levels of ROS may abolish the endogenous antioxidant system, leading to damage to proteins, lipids, and nucleic acids, resulting in cell apoptosis. Nevertheless, whether riboflavin plus UV light can trigger leukocyte apoptosis remains obscure. In this study, a pool-and-split design, ABO/D-matched lymphocytes treated with RF-PRT or UV light or left untreated. After treatment, the level of ROS and intracellular calcium were measured in samples. Changes in the protein expression of cleaved PARP, Bax, and Bcl-2 and the activities of caspase-3 and caspase-9 were determined by immunoblot analysis or luminometer, respectively. Cell apoptosis was evaluated by flow cytometry. The effect of ROS on apoptosis was assessed. The RF-PRT treatment significantly augmented ROS production, intracellular calcium concentration. The pro-apoptotic proteins expression levels of Bax, but did not the anti-apoptotic protein Bcl-2, were markedly increased after the RF-PRT treatment. Furthermore, the percentage of apoptotic cells was increased in RF-PRT-treated lymphocytes compared to UV-treated cells or untreated cells. Moreover, the inhibition of ROS generation partially neutralized the apoptosis effects of riboflavin plus UV treatment. These findings revealed that RF-PRT-treated lymphocytes significantly increase the proportion of apoptotic cells by promoting ROS generation delineation of the biochemical processes influenced by RF-PRT are a necessary step to provide novel insights into the riboflavin pathogen inactivation technology.

Systems Biology Understanding of the Effects of Lithium on Cancer.

Lithium has many widely varying biochemical and phenomenological effects, suggesting that a systems biology approach is required to understand its action. Multiple lines of evidence point to lithium as a significant factor in development of cancer, showing that understanding lithium action is of high importance. In this paper we undertake first steps toward a systems approach by analyzing mutual enrichment between the interactomes of lithium-sensitive enzymes and the pathways associated with cancer. This work integrates information from two important databases, STRING, and KEGG pathways. We find that for the majority of cancer pathways the mutual enrichment is statistically highly significant, reinforcing previous lines of evidence that lithium is an important influence on cancer.

An assessment of true and false positive detection rates of stepwise epistatic model selection as a function of sample size and number of markers.

Association studies have been successful at identifying genomic regions associated with important traits, but routinely employ models that only consider the additive contribution of an individual marker. Because quantitative trait variability typically arises from multiple additive and non-additive sources, utilization of statistical approaches that include main and two-way interaction marker effects of several loci in one model could lead to unprecedented characterization of these sources. Here we examine the ability of one such approach, called the Stepwise Procedure for constructing an Additive and Epistatic Multi-Locus model (SPAEML), to detect additive and epistatic signals simulated using maize and human marker data. Our results revealed that SPAEML was capable of detecting quantitative trait nucleotides (QTNs) at sample sizes as low as n = 300 and consistently specifying signals as additive and epistatic for larger sizes. Sample size and minor allele frequency had a major influence on SPAEML's ability to distinguish between additive and epistatic signals, while the number of markers tested did not. We conclude that SPAEML is a useful approach for providing further elucidation of the additive and epistatic sources contributing to trait variability when applied to a small subset of genome-wide markers located within specific genomic regions identified using a priori analyses.

Systems Biology Understanding of the Effects of Lithium on Affective and Neurodegenerative Disorders.

Lithium has many widely varying biochemical and phenomenological effects, suggesting that a systems biology approach is required to understand its action. Multiple lines of evidence point to lithium intake and consequent blood levels as important determinants of incidence of neurodegenerative disease, showing that understanding lithium action is of high importance. In this paper we undertake first steps toward a systems approach by analyzing mutual enrichment between the interactomes of lithium-sensitive enzymes and the pathways associated with affective and neurodegenerative disorders. This work integrates information from two important databases, STRING and KEGG pathways. We find that for the majority of neurodegenerative disorders the mutual enrichment is many times greater than chance, reinforcing previous lines of evidence that lithium is an important influence on incidence of neurodegeneration. Our work suggests rational prioritization for which disorders are likely to be most sensitive to lithium and identifies genes that are likely to be useful targets for therapy adjunct to lithium.

Competing pairing symmetries in a generalized two-orbital model for the pnictide superconductors.

We introduce and study an extended "t-U-J" two-orbital model for the pnictides that includes Heisenberg terms deduced from the strong coupling expansion. Including these J terms explicitly allows us to enhance the strength of the (π,0)-(0,π) spin order which favors the presence of tightly bound pairing states even in the small clusters that are here exactly diagonalized. The A(1g) and B(2g) pairing symmetries are found to compete in the realistic spin-ordered and metallic regime. The dynamical pairing susceptibility additionally unveils low-lying B(1g) states, suggesting that small changes in parameters may render any of the three channels stable.

Tunable ultra-deep subwavelength photolithography using a surface plasmon resonant cavity.

Using numerical simulations, we report an observation of a novel tunable ultra-deep subwavelength nanolithography technique using a surface plasmon resonant cavity formed by a metallic grating and a metallic thin-film layer separated by a photoresist layer. The tuning capability is implemented by varying the cavity length, from which surface plasmon interferometric patterns with inherently higher optical resolution than that of conventional surface plasmon techniques are generated in the cavity of photoresist layer. The physical origin of the tunability is analytically confirmed by the dispersion relation derived from the cavity system.