Detection and quantification of poliovirus infection using FTIR spectroscopy and cell culture

<p>Abstract</p> <p>Background</p> <p>In a globalized word, prevention of infectious diseases is a major challenge. Rapid detection of viable virus particles in water and other environmental samples is essential to public health risk assessment, homeland security and environmental protection. Current virus detection methods, especially assessing viral infectivity, are complex and time-consuming, making point-of-care detection a challenge. Faster, more sensitive, highly specific methods are needed to quantify potentially hazardous viral pathogens and to determine if suspected materials contain viable viral particles. Fourier transform infrared (FTIR) spectroscopy combined with cellular-based sensing, may offer a precise way to detect specific viruses. This approach utilizes infrared light to monitor changes in molecular components of cells by tracking changes in absorbance patterns produced following virus infection. In this work poliovirus (PV1) was used to evaluate the utility of FTIR spectroscopy with cell culture for rapid detection of infective virus particles.</p> <p>Results</p> <p>Buffalo green monkey kidney (BGMK) cells infected with different virus titers were studied at 1 - 12 hours post-infection (h.p.i.). A partial least squares (PLS) regression method was used to analyze and model cellular responses to different infection titers and times post-infection. The model performs best at 8 h.p.i., resulting in an estimated root mean square error of cross validation (RMSECV) of 17 plaque forming units (PFU)/ml when using low titers of infection of 10 and 100 PFU/ml. Higher titers, from 10³to 10⁶PFU/ml, could also be reliably detected.</p> <p>Conclusions</p> <p>This approach to poliovirus detection and quantification using FTIR spectroscopy and cell culture could potentially be extended to compare biochemical cell responses to infection with different viruses. This virus detection method could feasibly be adapted to an automated scheme for use in areas such as water safety monitoring and medical diagnostics.</p

Diversification linked to larval host plant in the butterfly Eumedonia eumedon

It is widely accepted that the relationship between phytophagous insects and their host plants influences insect diversification. However, studies addressed at documenting host-associated genetic differentiation (HAD) and the mechanisms that drive reproductive isolation in host-associated lineages (or host races) are still scarce relative to insect diversity. To uncover further evidence on the HAD processes in Lepidoptera, we investigated the genetic structure of the geranium argus butterfly (Eumedonia eumedon) and tested for isolation by ecology (IBE) vs. isolation by distance (IBD). Genomic data revealed an array of host races (three of them in the same mountain range, the Cantabrian Mountains, northern Iberia) at apparently distinct levels of reproductive isolation. We found a pattern of IBE mediated by HAD at both local and European scales, in which genetic differentiation between populations and individuals correlated significantly with the taxonomic relatedness of the host plants. IBD was significant only when considered at the wider European scale. We hypothesize that, locally, HAD between Geranium-feeding populations was caused (at least partially) by allochrony, that is via adaptation of adult flight time to the flowering period of each host plant species. Nevertheless, the potential reproductive isolation between populations using Erodium and populations using Geranium cannot be explained by allochrony or IBD, and other mechanisms are expected to be at play.Peer reviewe

The emission by dust and stars of nearby galaxies in the Herschel KINGFISH survey

Using new far-infrared imaging from the Herschel Space Observatory with ancillary data from ultraviolet (UV) to submillimeter wavelengths, we estimate the total emission from dust and stars of 62 nearby galaxies in the KINGFISH survey in a way that is as empirical and model independent as possible. We collect and exploit these data in order to measure from the spectral energy distributions (SEDs) precisely how much stellar radiation is intercepted and re-radiated by dust, and how this quantity varies with galaxy properties. By including SPIRE data, we are more sensitive to emission from cold dust grains than previous analyses at shorter wavelengths, allowing for more accurate estimates of dust temperatures and masses. The dust/stellar flux ratio, which we measure by integrating the SEDs, has a range of nearly three decades (from 10(-2.2) to 10(0.5)). The inclusion of SPIRE data shows that estimates based on data not reaching these far-IR wavelengths are biased low by 17% on average. We find that the dust/stellar flux ratio varies with morphology and total infrared (IR) luminosity, with dwarf galaxies having faint luminosities, spirals having relatively high dust/stellar ratios and IR luminosities, and some early types having low dust/stellar ratios. We also find that dust/stellar flux ratios are related to gas-phase metallicity ((log(f(dust)/f(*)) over bar) = -0.66 +/- 0.08 and -0.22 +/- 0.12 for metal-poor and intermediate-metallicity galaxies, respectively), while the dust/stellar mass ratios are less so (differing by approximate to 0.2 dex); the more metal-rich galaxies span a much wider range of the flux ratios. In addition, the substantial scatter between dust/stellar flux and dust/stellar mass indicates that the former is a poor proxy of the latter. Comparing the dust/stellar flux ratios and dust temperatures, we also show that early types tend to have slightly warmer temperatures (by up to 5 K) than spiral galaxies, which may be due to more intense interstellar radiation fields, or possibly to different dust grain compositions. Finally, we show that early types and early-type spirals have a strong correlation between the dust/stellar flux ratio and specific star formation rate, which suggests that the relatively bright far-IR emission of some of these galaxies is due to ongoing (if limited) star formation as well as to the radiation field from older stars, which is heating the dust grains

Dust and Gas in the Magellanic Clouds from the HERITAGE Herschel Key Project. II. Gas-to-Dust Ratio Variations across ISM Phases

The spatial variations of the gas-to-dust ratio (GDR) provide constraints on the chemical evolution and lifecycle of dust in galaxies. We examine the relation between dust and gas at 10-50 pc resolution in the Large and Small Magellanic Clouds (LMC and SMC) based on Herschel far-infrared (FIR), H I 21 cm, CO, and Halpha observations. In the diffuse atomic ISM, we derive the gas-to-dust ratio as the slope of the dust-gas relation and find gas-to-dust ratios of 380+250-130 in the LMC, and 1200+1600-420 in the SMC, not including helium. The atomic-to-molecular transition is located at dust surface densities of 0.05 Mo pc-2 in the LMC and 0.03 Mo pc-2 in the SMC, corresponding to AV ~ 0.4 and 0.2, respectively. We investigate the range of CO-to-H2 conversion factor to best account for all the molecular gas in the beam of the observations, and find upper limits on XCO to be 6x1020 cm-2 K-1 km-1 s in the LMC (Z=0.5Zo) at 15 pc resolution, and 4x 1021 cm-2 K-1 km-1 s in the SMC (Z=0.2Zo) at 45 pc resolution. In the LMC, the slope of the dust-gas relation in the dense ISM is lower than in the diffuse ISM by a factor ~2, even after accounting for the effects of CO-dark H2 in the translucent envelopes of molecular clouds. Coagulation of dust grains and the subsequent dust emissivity increase in molecular clouds, and/or accretion of gas-phase metals onto dust grains, and the subsequent dust abundance (dust-to-gas ratio) increase in molecular clouds could explain the observations. In the SMC, variations in the dust-gas slope caused by coagulation or accretion are degenerate with the effects of CO-dark H2. Within the expected 5--20 times Galactic XCO range, the dust-gas slope can be either constant or decrease by a factor of several across ISM phases. Further modeling and observations are required to break the degeneracy between dust grain coagulation, accretion, and CO-dark H2

SimCol3D -- 3D Reconstruction during Colonoscopy Challenge

Colorectal cancer is one of the most common cancers in the world. While colonoscopy is an effective screening technique, navigating an endoscope through the colon to detect polyps is challenging. A 3D map of the observed surfaces could enhance the identification of unscreened colon tissue and serve as a training platform. However, reconstructing the colon from video footage remains unsolved due to numerous factors such as self-occlusion, reflective surfaces, lack of texture, and tissue deformation that limit feature-based methods. Learning-based approaches hold promise as robust alternatives, but necessitate extensive datasets. By establishing a benchmark, the 2022 EndoVis sub-challenge SimCol3D aimed to facilitate data-driven depth and pose prediction during colonoscopy. The challenge was hosted as part of MICCAI 2022 in Singapore. Six teams from around the world and representatives from academia and industry participated in the three sub-challenges: synthetic depth prediction, synthetic pose prediction, and real pose prediction. This paper describes the challenge, the submitted methods, and their results. We show that depth prediction in virtual colonoscopy is robustly solvable, while pose estimation remains an open research question

An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks

Over the past few years, Intelligent Spaces (ISs) have received the attention of many Wireless Sensor Network researchers. Recently, several studies have been devoted to identify their common capacities and to set up ISs over these networks. However, little attention has been paid to integrating Fuzzy Rule-Based Systems into collaborative Wireless Sensor Networks for the purpose of implementing ISs. This work presents a distributed architecture proposal for collaborative Fuzzy Rule-Based Systems embedded in Wireless Sensor Networks, which has been designed to optimize the implementation of ISs. This architecture includes the following: (a) an optimized design for the inference engine; (b) a visual interface; (c) a module to reduce the redundancy and complexity of the knowledge bases; (d) a module to evaluate the accuracy of the new knowledge base; (e) a module to adapt the format of the rules to the structure used by the inference engine; and (f) a communications protocol. As a real-world application of this architecture and the proposed methodologies, we show an application to the problem of modeling two plagues of the olive tree: prays (olive moth, Prays oleae Bern.) and repilo (caused by the fungus Spilocaea oleagina). The results show that the architecture presented in this paper significantly decreases the consumption of resources (memory, CPU and battery) without a substantial decrease in the accuracy of the inferred values

Development and evaluation of prefabricated antipronation foot orthosis

Our aim was to develop and evaluate a new antipronation foot orthosis that addressed problems perceived by clinicians and users with existing foot orthoses. Clinicians and users were engaged to develop a user specification for the orthosis, and orthotic geometry and materials were developed using clinical reasoning. The orthotic material properties were tested and the ability of the orthosis to reduce foot pronation evaluated on 27 individuals. Clinicians expressed concern that current prefabricated orthoses often did not offer sufficient support to the foot because of a combination of the shape and materials used, and users concurred but also highlighted issues of durability and hygiene. The geometry of the new orthosis was, therefore, adjusted to enable individual foot size orthoses to be produced. A material was selected that was harder and more durable than materials used in many prefabricated orthoses. When the new orthosis was being worn, maximum rearfoot eversion was reduced in both walking (mean reduction 3.8 degrees, p < 0.001) and running (mean reduction 2.5 degrees, p < 0.001). Through a structured process, orthotic design decisions were made that addressed the specific concerns of clinicians and users and the new orthosis was proven to reduce rearfoot pronation

Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201