Macrophage-Mediated Melanoma Reduction after HP-NAP Treatment in a Zebrafish Xenograft Model

The Helicobacter pylori Neutrophil Activating Protein (HP-NAP) is endowed with immunomodulatory properties that make it a potential candidate for anticancer therapeutic applications. By activating cytotoxic Th1 responses, HP-NAP inhibits the growth of bladder cancer and enhances the anti-tumor activity of oncolytic viruses in the treatment of metastatic breast cancer and neuroendocrine tumors. The possibility that HP-NAP exerts its anti-tumor effect also by modulating the activity of innate immune cells has not yet been explored. Taking advantage of the zebrafish model, we examined the therapeutic efficacy of HP-NAP against metastatic human melanoma, limiting the observational window to 9 days post-fertilization, well before the maturation of the adaptive immunity. Human melanoma cells were xenotransplanted into zebrafish embryos and tracked in the presence or absence of HP-NAP. The behavior and phenotype of macrophages and the impact of their drug-induced depletion were analyzed exploiting macrophage-expressed transgenes. HP-NAP administration efficiently inhibited tumor growth and metastasis and this was accompanied by strong recruitment of macrophages with a pro-inflammatory profile at the tumor site. The depletion of macrophages almost completely abrogated the ability of HP-NAP to counteract tumor growth. Our findings highlight the pivotal role of activated macrophages in counteracting melanoma growth and support the notion that HP-NAP might become a new biological therapeutic agent for the treatment of metastatic melanomas.     

Cross-Omics Analysis of Fenugreek Supplementation Reveals Beneficial Effects Are Caused by Gut Microbiome Changes Not Mammalian Host Physiology

Herbal remedies are increasing in popularity as treatments for metabolic conditions such as obesity and Type 2 Diabetes. One potential therapeutic option is fenugreek seeds (Trigonella foenum-graecum), which have been used for treating high cholesterol and Type 2 diabetes. A proposed mechanism for these benefits is through alterations in the microbiome, which impact mammalian host metabolic function. This study used untargeted metabolomics to investigate the fenugreek-induced alterations in the intestinal, liver, and serum profiles of mice fed either a 60% high-fat or low-fat control diet each with or without fenugreek supplementation (2% w/w) for 14 weeks. Metagenomic analyses of intestinal contents found significant alterations in the relative composition of the gut microbiome resulting from fenugreek supplementation. Specifically, Verrucomicrobia, a phylum containing beneficial bacteria which are correlated with health benefits, increased in relative abundance with fenugreek. Metabolomics partial least squares discriminant analysis revealed substantial fenugreek-induced changes in the large intestines. However, it was observed that while the magnitude of changes was less, significant modifications were present in the liver tissues resulting from fenugreek supplementation. Further analyses revealed metabolic processes affected by fenugreek and showed broad ranging impacts in multiple pathways, including carnitine biosynthesis, cholesterol and bile acid metabolism, and arginine biosynthesis. These pathways may play important roles in the beneficial effects of fenugreek.     

Development of a Demand Driven Hydro-climatic Model for Drought Planning

In recent years, droughts with increasing severity and frequency have been experienced around the world due to climate change effects. Water planning and management during droughts needs to deal with water demand variability, uncertainties in streamflow prediction, conflicts over water resources allocation, and the absence of necessary emergency schemes in drought situations. Reservoirs could play an important role in drought mitigation; therefore, development of an algorithm for operation of reservoirs in drought periods could help to mitigate the drought impacts by reducing the expected water shortages. For this purpose, the probable drought’s characteristics and their variations in response to factors such as climate change should be incorporated. This study aims at developing a contingency planning scheme for operation of reservoirs in drought periods using hedging rules with the objective of decreasing the maximum water deficit. The case study for evaluation of the performance of the proposed algorithm is the Sattarkhan reservoir in the Aharchay watershed, located in the northwestern part of Iran. The trend evaluations of the hydro-climatic variables show that the climate change has already affected streamflow in the region and has increased water scarcity and drought severity. To incorporate the climate change study in reservoir planning; streamflow should be simulated under climate change impacts. For this purpose, the climatic variables including temperature and precipitation in the future under climate change impacts are simulated using downscaled GCM (General Circulation Model) outputs to derive scenarios for possible future drought events. Then a hydrological model is developed to simulate the river streamflow, based on the downscaled data. The results show that the proposed methodology leads to less water deficit and decreases the drought damages in the study area.     

pH Responsive Abelmoschus esculentus Mucilage and Administration of Methotrexate: In-Vitro Antitumor and In-Vivo Toxicity Evaluation

The rapid progression in biomaterial nanotechnology apprehends the potential of non-toxic and potent polysaccharide delivery modules to overcome oral chemotherapeutic challenges. The present study is aimed to design, fabricate and characterize polysaccharide nanoparticles for methotrexate (MTX) delivery. The nanoparticles (NPs) were prepared by Abelmoschus esculentus mucilage (AEM) and chitosan (CS) by the modified coacervation method, followed by ultra-sonification. The NPs showed much better pharmaceutical properties with a spherical shape and smooth surface of 213.4–254.2 nm with PDI ranging between 0.279–0.485 size with entrapment efficiency varying from 42.08 ± 1.2 to 72.23 ± 2.0. The results revealed NPs to possess positive zeta potential and a low polydispersity index (PDI). The in-vitro drug release showed a sustained release of the drug up to 32 h with pH-dependence. Blank AEM -CS NPs showed no in-vivo toxicity for a time duration of 14 days, accompanied by high cytotoxic effects of optimized MTX loaded NPs against MCF-7 and MD-MBA231 cells by MTT assay. In conclusion, the findings advocated the therapeutic potential of AEM/CS NPs as an efficacious tool, offering a new perspective for pH-responsive routing of anticancer drugs with tumor cells as a target.     

Underlay Device to Device Communication with Imperfect Interference Channel Knowledge

The objective of any night vision system is to enable a person to see in the dark. A low-contrast image puts a contrast constraint on the human observer visibility at night. This is the basic reason for the large number of accidents at night. This research presents two proposed approaches to enhance the visibility of the infrared (IR) night vision images through an efficient histogram processing. The first approach is based on contrast limited adaptive histogram equalization. The second proposed approach depends on histogram matching. The histogram matching uses a reference visual image for converting night vision images into good quality images. The obtained results are evaluated with quality metrics such as entropy, average gradient, contrast improvement factor and sobel edge magnitude.     

BSig: evaluating the statistical significance of biclustering solutions

Statistical evaluation of biclustering solutions is essential to guarantee the absence of spurious relations and to validate the high number of scientific statements inferred from unsupervised data analysis without a proper statistical ground. Most biclustering methods rely on merit functions to discover biclusters with specific homogeneity criteria. However, strong homogeneity does not guarantee the statistical significance of biclustering solutions. Furthermore, although some biclustering methods test the statistical significance of specific types of biclusters, there are no methods to assess the significance of flexible biclustering models. This work proposes a method to evaluate the statistical significance of biclustering solutions. It integrates state-of-the-art statistical views on the significance of local patterns and extends them with new principles to assess the significance of biclusters with additive, multiplicative, symmetric, order-preserving and plaid coherencies. The proposed statistical tests provide the unprecedented possibility to minimize the number of false positive biclusters without incurring on false negatives, and to compare state-of-the-art biclustering algorithms according to the statistical significance of their outputs. Results on synthetic and real data support the soundness and relevance of the proposed contributions, and stress the need to combine significance and homogeneity criteria to guide the search for biclusters.     

A Review of Pathways for Building Fire Spread in the Wildland Urban Interface Part II: Response of Components and Systems and Mitigation Strategies in the United States

Structure loss in wildland fires has significantly increased over the past few decades, affected by increased development in rural areas, changing fuel management policies, and climate change, all of which are projected to increase in the future. This paper is Part II of a two-part review, which presents a summary of fundamental and applied research on pathways to fire spread in the wildland urban interface. Part I discussed the fundamentals of wildland fire spread via radiative heat transfer, direct flame contact, and firebrand exposure. Here in Part II, we cover the response of building components and systems, as well as mitigation strategies used to prevent fire spread into and within communities in the United States. Post-fire investigations, full-scale structural testing, individual component testing, and combined systems or assembly testing have been used to identify building component and system vulnerabilities such as roofs, vents, siding, decks, fences, and mulch. Using results from these tests and investigations at different scales, some knowledge has been gained on specific vulnerabilities and the effectiveness of mitigation strategies, but a quantitative framework has not yet been established. On a community level, the layout of structures and the space between them has been shown to be incredibly important in mitigating wildfire risk. More locally, defensible space around homes has been effective in mitigating exposure from both radiation and direct flame contact. Firebrands still remain a challenge; however, many design recommendations have been proposed to harden structures against firebrand exposures. Recommendations for future research and development are also presented.     

Using the red-near infrared spectral to estimate ground cover based on vegetative indices

Rapid and accurate estimation of Ground Cover (GC) at regional and global scales for agricultural management application is only possible by using remote sensing (RS). In this study, two Vegetation Indices (VIs) including the Perpendicular Vegetation Index (PVI) and Normalized Difference Vegetation Index (NDVI) were used for estimating GC. Since the parameters of the bare soil line have an important role in calculating GC based on PVI, this line was extracted based on the red-NIRmin (minimum near infrared) method with different intervals (0.0001, 0.0005, and 0.0010). In addition to traditional statistics such as Root Mean Square Error (RMSE), the sensitivity analysis (S) was also used to sharpen the accuracy of the models' estimations. The results indicated that the PVI-based method, in contrast to the NDVI-based approach, had a better performance in estimating GC of wheat. The highest correlation between the observed GC and the estimated GC based on PVI method was achieved in interval length of 0.0005 (R2 = 0.91) with RMSE equal to 8.82. This regression line (GCEST = -3.47 + 0.96 GCOBS) was not significantly different from the 1:1 line. As expected, the best estimation was achieved when the sensitivity of estimated GC based on PVI (length of the interval: 0.0005) was almost constant and low compared to the other models.