Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Topical Treatment for Pseudomonas aeruginosa Wound Infections by Quorum-Sensing Inhibitors Mediated by Poly(amidoamine) (PAMAM) Dendrimers

Abstract : During this performance period, we have made significant progress on the following Tasks as stated in SOW: 1, 2, 4, 5, 6, 7 and 8. For Specific Aim 1, we have synthesized 18 QSI-PAMAM complexes by encapsulation (Task 1), conjugation (Task 2), or both. For Specific Aim 2, we have established all the protocols to measure planktonic and biofilm growth of PA (Task 5), turnover of PAMAM in PA (Task 6), quinolone signals by HPLC-MS (Task 7), and extracellular virulence factors (Task 8). The most significant finding was the specific inhibition of PAMAM dendrimers on Pseudomonas aeruginosa (PA) biofilm formation and growth. This is significant because PA in the biofilm form is known to be up to 1000 fold more resistant antibiotic treatments. We systematically analyzed the effects of surface charge and particle size on PA biofilm. PAMAM dendrimers with more positive charges on the surface and bigger particle sizes exhibited more potent inhibition. Confocal fluorescent microscopy showed that PAMAM dendrimers also altered the morphology of PA biofilm. In addition, combination of PAMAM dendrimers also significantly enhanced the inhibition of PA biofilm growth by antibiotic such as amikacin.
Depression in cancer patients: Pathogenesis, implications and treatment (Review)

Depression is a common comorbidity in cancer cases, affecting >10% of patients. A cancer diagnosis is life-changing, and is a source of considerable psychological and emotional stress. Non-pathological sadness may be a normal response to a cancer diagnosis, however, stress beyond the coping mechanisms of patients may result in major depressive disorder. The current review, in addition to the obvious psychosocial elements of depression, explores its biological mechanisms, including tissue damage, inflammatory mediators and the chronic stress response, and how these immune and endocrine pathways may underlie depression in cancer. Possible iatrogenic causes of depression in cancer are also explored. There is a strong need to identify and treat depression in cancer patients in order to increase quality of life and reduce mortality. The most popular clinical and potential future biochemical screening tools for depression in cancer are briefly discussed. The interventions used will vary for every patient, but may include psychosocial therapies or pharmacotherapy; however, a paucity of research on the most effective management of depression in cancer means the optimal combination of therapies is unknown. Selection of antidepressants should be carefully considered, given the common side effects of chemotherapy (such as nausea), and the necessity to avoid serious interactions, including reducing the effectiveness of chemotherapeutic drugs. The possible link between the chronic stress response, which may predispose patients to depression, and the risk of mortality from cancer is also explored. The complex interactions between the endocrine, nervous and immune systems, which continue to be elucidated, may offer the opportunity for the development of more rapid and efficacious treatments for depression in cancer in the future.
Introduction of midkine gene into human bladder cancer cells enhances their malignant phenotype but increases their sensitivity to antiangiogenic therapy.

PURPOSE Midkine (MK) is a member of a family of heparin-binding growth factors, which was reported to have an important role in angiogenesis. Although MK was reported to be associated with bladder cancer progression, the functional significance of MK expression in bladder cancer progression has not been elucidated. The objectives of this study were to determine whether overexpression of MK in bladder cancer cells enhances their malignant potential and to evaluate the inhibitory effect of the antiangiogenic agent TNP-470 on the growth of MK-overexpressing bladder cancer cells in vivo. EXPERIMENTAL DESIGN We introduced the MK gene into human bladder cancer UM-UC-3 cells that do not secrete a detectable level of MK protein and generated the MK-overexpressing cell line UM-UC-3/MK. The biological activity of secreted MK was evaluated using a human umbilical vein endothelial cell proliferation assay. To investigate the in vivo effects of MK overexpression on tumor growth, each cell line was injected s.c. and orthotopically into nude mice. To evaluate the therapeutic effects of the antiangiogenic agent, mice were given TNP-470 after s.c. injection of each cell line. The microvessel density of tumors was quantitated by immunohistochemistry of CD31. RESULTS The heparin affinity-purified conditioned media of UM-UC-3/MK cells significantly enhanced human umbilical vein endothelial cell proliferation. MK expression had no effect on in vitro growth but conferred a growth advantage on both s.c. and orthotopic tumors in vivo. Furthermore, enhanced tumor growth was closely associated with increased microvessel density. Significant inhibition of tumor growth by TNP-470 treatment was observed only in UM-UC-3/MK tumors and not in control tumors. CONCLUSIONS We demonstrated that overexpression of the MK gene causes an increase in the angiogenic activity of cells through vascular endothelial cell growth, resulting in enhanced malignant potential of human bladder cancer cells. Moreover, the present findings suggest that TNP-470 could be used as a novel therapeutic adjunct to conventional agents for patients with advanced bladder cancer overexpressing MK.
Nanofabrication using a stencil mask

We describe tests of a technique to fabricate nanostructures by the evaporation of metal through a stencil mask etched in a suspended silicon nitride membrane. Collimated evaporation through the mask gives metal dots less than 15 nm in diameter and lines 15–20 nm wide. We have investigated the extent of hole clogging and the factors which determine the ultimate resolution of the technique.
A MUSIC like DOA estimation method for signals with low SNR

A new kind of noise subspace based direction-of-arrival (DOA) estimation method is proposed. Unlike the MUSIC algorithm , the novel MUSIC like method use signal subspace estimated by multi-stage Wiener filter (MSWF) instead of array steering vectors for orthogonality test. Simulation shows that the proposed method offers improvements in precision and resolution performance for signals with low SNR, compared to MUSIC and ESPRIT algorithms.
Boolean matching for large libraries

Boolean matching tackles the problem whether a subcircuit of a boolean network can be substituted by a cell from a cell library. In previous approaches each pair of a subcircuit and a cell is tested for NPN equivalence. This becomes very expensive if the cell library is large. In our approach the time complexity for matching a subcircuit against a library L is almost independent of the size of L. CPU time also remains small for matching a subcircuit against the huge set of functions obtained by bridging and fixing cell inputs; but the use of these functions in technology mapping is very profitable. Our method is based on a canonical representative for each NPN equivalence class. We show how this representative can be computed efficiently and how it can be used for matching a boolean function against a set of library functions.
The Filbert Matrix

A Filbert matrix is a matrix whose (i,j) entry is 1/F_(i+j-1), where F_n is the nth Fibonacci number. The inverse of the n by n Filbert matrix resembles the inverse of the n by n Hilbert matrix, and we prove that it shares the property of having integer entries. We prove that the matrix formed by replacing the Fibonacci numbers with the Fibonacci polynomials has entries which are integer polynomials. We also prove that certain Hankel matrices of reciprocals of binomial coefficients have integer entries, and we conjecture that the corresponding matrices based on Fibonomial coefficients have integer entries. Our method is to give explicit formulae for the inverses.
An Impression on Current Developments in the Technology, Chemistry, and Biological Activities of Ginger (Zingiber officinale Roscoe)

Ginger rhizome (Zingiber officinale Roscoe) is widely cultivated as a spice for its aromatic and pungent components. The essential oil and oleoresins from ginger are valuable products responsible for the characteristic flavor and pungency. Both are used in several food products such as soft beverages and also in many types of pharmaceutical formulations. More than 100 compounds have been reported from ginger, some of which are isolated and characterized, others are tentatively identified by GC-MS and / or LC-MS. [6]-Gingerol, the major gingerol in ginger rhizomes, has been found to possess many interesting pharmacological and physiological activities, such as anti-inflammatory, analgesic, and cardiotonic effects. Ginger is considered as “generally recognized as safe” (GRAS) by Food and Drug Administration (FDA), USA. Due to all these properties, ginger has gained considerable attention in developed countries in recent years, especially for its use in the treatment of inflammatory conditions. The present review is a persuasive presentation of the current information on processing, chemistry, biological activities, and medicinal uses of ginger. Further studies are required for the validation of the beneficial uses. Formulation for novel products and new usages may emerge in the years to come, based on the revealed results of various studies.
Nanoindentation study of MAO coatings developed by dual electrolytes

The micro arc oxidation (MAO) process is one of the most industrially accepted, prospective methods to design and develop microstruturally integrated, intrinsically generated oxide/ceramic coating over Mg alloys. Here we report, the surface engineering of AZ31 Mg alloy to form MAO coatings by silicate and phosphate based electrolytes. The microstructural examinations of the MAO coatings were carried out by scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) analysis. Further, the nanoindentation studies revealed that the MAO coatings had nanohardness (H) and Young's modulus (E) values as high as about 3–7 times and 1·5–2·5 times those of the as received AZ31 Mg alloy respectively. Both H and E values gradually increased from virgin Mg substrate end to the surface coating end. Further, sealing by hot water did not affect the H and E values of the MAO coatings.
The Effect of Expected Income on Individual Migration Decisions

The paper develops a tractable econometric model of optimal migration, focusing on expected income as the main economic influence on migration. The model improves on previous work in two respects: it covers optimal sequences of location decisions (rather than a single once-for-all choice), and it allows for many alternative location choices. The model is estimated using panel data from the NLSY on white males with a high school education. Our main conclusion is that interstate migration decisions are influenced to a substantial extent by income prospects. The results suggest that the link between income and migration decisions is driven both by geographic differences in mean wages and by a tendency to move in search of a better locational match when the income realization in the current location is unfavorable.
How Accurate Can Any Regression Procedure Be ?

Various parametric and nonparametric regression procedures have been constructed according to diierent possible characteristics of the underlying regression function. To reduce the dependence on subjective assumptions, the theme of adaptive estimation is to construct a procedure that provides an accurate estimate of the regression function for various scenarios without knowing which one describes the data well. A closely related question is: Given a regression procedure, how many regression functions are estimated accurately? In this work, for a given sequence of prescribed estimation accuracy (in sample size), we give an upper bound (in terms of metric entropy) on the number of regression functions for which the accuracy is achieved. A consequence is that if one demands near optimal performance for a target class of regression functions, then the same accuracy can not be achieved for many additional regression functions. This has a negative implication on adaptive estimation. The main result is also applied to show that as far as polynomial rates of convergence are concerned, any regression procedure is essentially no better than a method based on sparse approximation.
Using the quaternion's representation of individuals in swarm intelligence and evolutionary computation

This paper introduces a novel idea for representation of individuals using quaternions in swarm intelligence and evolutionary algorithms. Quaternions are a number system, which extends complex numbers. They are successfully applied to problems of theoretical physics and to those areas needing fast rotation calculations. We propose the application of quaternions in optimization, more precisely, we have been using quaternions for representation of individuals in Bat algorithm. The preliminary results of our experiments when optimizing a test-suite consisting of ten standard functions showed that this new algorithm significantly improved the results of the original Bat algorithm. Moreover, the obtained results are comparable with other swarm intelligence and evolutionary algorithms, like the artificial bees colony, and differential evolution. We believe that this representation could also be successfully applied to other swarm intelligence and evolutionary algorithms.
Glucose Metabolism in the Insula and Cingulate Is Affected by Systemic Inflammation in Humans

Depression is associated with systemic inflammation, and the systemic inflammation caused by endotoxin administration elicits mild depressive symptoms such as fatigue and reduced interest. The neural correlates of depressive symptoms that result from systemic inflammation are poorly defined. The aim of this study was to use 18F-FDG PET to identify brain regions involved in the response to endotoxin administration in humans. Methods: Nine healthy subjects received double-blind endotoxin (0.8 ng/kg) and placebo on different days. 18F-FDG PET was used to measure differences in the cerebral metabolic rate of glucose in the following regions of interest: insula, cingulate, and amygdala. Serum levels of tumor necrosis factor-α and interleukin-6 were used to gauge the systemic inflammatory response, and depressive symptoms were measured with the Montgomery-Åsberg Depression Rating Scale and other scales. Results: Endotoxin administration was associated with an increase in Montgomery-Åsberg Depression Rating Scale, increased fatigue, reduced social interest, increased levels of inflammatory cytokines, higher normalized glucose metabolism (NGM) in the insula, and, at a trend level, lower NGM in the cingulate. Secondary analyses of insula and cingulate subregions indicated that these changes were driven by the right anterior insula and the right anterior cingulate. There was a negative correlation between peak cytokine levels and change in social interest and between peak cytokine levels and change in insula NGM. There was a positive correlation between the change in NGM in the insula and change in social interest. Conclusion: Systemic inflammation in humans causes an increase in depressive symptoms and concurrent changes in glucose metabolism in the insula and cingulate—brain regions that are involved in interoception, positive emotionality, and motivation.
Finite-time Attractive Ellipsoid Method using Implicit Lyapunov Functions

A finite-time version, based on Implicit Lyapunov Functions (ILF), for the Attractive Ellipsoid Method (AEM) is developed. Based on this, a robust control scheme is presented to ensure finite-time convergence of the solutions of a chain of integrators with bounded output perturbations to a minimal ellipsoidal set. The control parameters are obtained by solving a minimization problem of the “size” of the ellipsoid subject to a set of Linear Matrix Inequalities (LMI's) constraints, and by applying the implicit function theorem. A numerical example is presented to support the implementability of these theoretical results.
U-Shaped Relation between Plasma Oxytocin Levels and Behavior in the Trust Game

Trust underpins much of social and economic exchanges across human societies. In experimental economics, the Trust Game has served as the workhorse for the study of trust in a controlled incentivized setting. Recent evidence using intranasal drug administration, aka ‘sniffing’, suggests that oxytocin (OT) can function as a social hormone facilitating trust and other affiliative behaviors. Here we hypothesized that baseline plasma OT is a biomarker that partially predicts the degree of trust and trustworthiness observed in the trust game. Using a large sample of 1,158 participants, we observed a significant U-shaped relationship between plasma OT with the level of trust, and marginally with the level of trustworthiness, especially among males. Specifically, subjects with more extreme levels of plasma OT were more likely to be trusting as well as trustworthy than those with moderate levels of plasma OT. Our results contribute to a deeper understanding of the biological basis of human trust and underscore the usefulness of peripheral plasma OT measures in characterizing human social behavior.
State Complexity of Combined Operations with Two Basic Operations

This paper studies the state complexity of (L 1 L 2) R , L 2008] for the state complexity of (L 1 L 2) R coincides with the lower bound and is thus the state complexity of this combined operation by providing some witness DFAs. Also, we show that, unlike most other cases, due to the structural properties of the result of the first operation of the combinations L R 1 L 2 , L * 1 L 2 , and (L 1 ∪ L 2)L 3 , the state complexity of each of these combined operations is close to the mathematical composition of the state complexities of the component operations. Moreover, we show that the state complexities of (L 1 ∩ L 2)L 3 , L 1 L 2 ∩ L 3 , and L 1 L 2 ∪ L 3 are exactly equal to the mathematical compositions of the state complexities of their component operations in the general cases. We also include a brief survey that summarizes all state complexity results for combined operations with two basic operations.
Multi-faceted Reliability Assessment Techniques: An Industrial Case Study

This case study describes the application of three combined assessment reference models that result in a measurable and reproducible insight in quality aspects of complex systems. In this case insight is given in the software reliability an electronic control system. A multifaceted assessment technique is presented that meets both the CMMi and Automotive-SPICE process assessment requirements and identifies the practices in the product lifecycle processes that might introduce not-found faults in software. An in depth TMMi based test assessment technique identifies reasons why not allintroduced faults are found. As the third technique an ISO25010 based code assessment identifies reliability risk areas in the software code. Qualitative assessment data obtained from documentation study and interviews is translated in a reproducible software reliability number. Based on detailed observations and findings improvement proposals are reported that increase obviously the overall reliability number when implemented. The three presented assessment techniques are commonly applied in high tech industry as well as in automotive industry however not in the described powerful combination. The multi-faceted assessment techniques can rather simply be made more specific for the automotive application by exchanging the CMMi reference model by Automotive-SPICE.
Loss of SPARC dysregulates basal lamina assembly to disrupt larval fat body homeostasis in Drosophila melanogaster

Background: SPARC is a collagen‐binding glycoprotein whose functions during early development are unknown. We previously reported that SPARC is expressed in Drosophila by hemocytes and the fat body (FB) and enriched in basal laminae (BL) surrounding tissues, including adipocytes. We sought to explore if SPARC is required for proper BL assembly in the FB. Results: SPARC deficiency leads to larval lethality, associated with remodeling of the FB. In the absence of SPARC, FB polygonal adipocytes assume a spherical morphology. Loss‐of‐function clonal analyses revealed a cell‐autonomous accumulation of BL components around mutant cells that include collagen IV (Col lV), Laminin, and Perlecan. Ultrastructural analyses indicate SPARC‐deficient adipocytes are surrounded by an aberrant accumulation of a fibrous extracellular matrix. Conclusions: Our data indicate a critical requirement for SPARC for the proper BL assembly in Drosophila FB. Since Col IV within the BL is a prime determinant of cell shape, the rounded appearance of SPARC‐deficient adipocytes is due to aberrant assembly of Col IV. Developmental Dynamics 244:540–552, 2015. © 2014 Wiley Periodicals, Inc.
A Proposed Approach for Image Compression based on Wavelet Transform and Neural Network

Over the last years, wavelet theory has been used with great success in a wide range of applications as signal de-noising and image compression. An ideal image compression system must yield high-quality compressed image with high compression ratio. This paper attempts to find the most useful wavelet function to compress an image among the existing members of wavelet families. Our idea is that a backpropagation neural network is trained to select the suitable wavelet function between the two families: orthogonal (Haar) and biorthogonal (bior4.4), to be used to compress an image efficiently and accurately with an ideal and optimum compression ratio. The simulation results indicated that the proposed technique can achieve good compressed images in terms of peak signal to noise ratio (PSNR) and compression ratio (t) in comparison with random selection of the mother wavelet.
Stochastic Signal Modeling Techniques for Stock Market Prediction

Autocorrelation measures the degree to which a current variable is correlated to the past values. Autocorrelation can be measured by running a regression equation. The study employs this temporal correlation that exists between the various stock markets related variables to predict future trends and prices, using two stochastic signal modeling processes. Data for stocks listed on the NASDAQ was scraped from the Yahoo! Finance website. Autoregressive (AR) and Autoregressive Moving Average (ARMA) techniques have been used to predict the next day’s closing price using a time series input of the previous L days. Autoregression models the dependence of the variable to be predicted with its own lagged terms while Autoregressive Moving Average builds on Autoregression by allowing for the introduction of the Moving Average model which includes lagged terms on the residuals. The mean square error of the two was compared. The study concludes that the two models should be used in consonance for accurately modeling the magnitude and the direction of the movement in the variable to be predicted. General Terms Prediction techniques, Digital Signal Processing, Stochastic Signal Modeling, Power Spectral Density, Autocorrelation