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Point-of-care and in-vivo bio-diagnostic tools are the current need for the present critical scenarios in the healthcare industry. The past few decades have seen a surge in research activities related to solving the challenges associated with precise on-site bio-sensing. Cutting-edge fiber optic technology enables the interaction of light with functionalized fiber surfaces at remote locations to develop a novel, miniaturized and cost-effective lab on fiber technology for bio-sensing applications. The recent remarkable developments in the field of nanotechnology provide innumerable functionalization methodologies to develop selective bio-recognition elements for label free biosensors. These exceptional methods may be easily integrated with fiber surfaces to provide highly selective light-matter interaction depending on various transduction mechanisms. In the present review, an overview of optical fiber-based biosensors has been provided with focus on physical principles used, along with the functionalization protocols for the detection of various biological analytes to diagnose the disease. The design and performance of these biosensors in terms of operating range, selectivity, response time and limit of detection have been discussed. In the concluding remarks, the challenges associated with these biosensors and the improvement required to develop handheld devices to enable direct target detection have been highlighted.
Selection of high-performance lines with respect to traits of interest is a key step in plant breeding. Genomic prediction allows to determine the genomic estimated breeding values of unseen lines for trait of interest using genetic markers, e.g. single-nucleotide polymorphisms (SNPs), and machine learning approaches, which can therefore shorten breeding cycles, referring to genomic selection (GS). Here, we applied GS approaches in two populations of Solanaceous crops, i.e. tomato and pepper, to predict morphometric and colorimetric traits. The traits were measured by using scoring-based conventional descriptors (CDs) as well as by Tomato Analyzer (TA) tool using the longitudinally and latitudinally cut fruit images. The GS performance was assessed in cross-validations of classification-based and regression-based machine learning models for CD and TA traits, respectively. The results showed the usage of TA traits and tag SNPs provide a powerful combination to predict morphology and color-related traits of Solanaceous fruits. The highest predictability of 0.89 was achieved for fruit width in pepper, with an average predictability of 0.69 over all traits. The multi-trait GS models are of slightly better predictability than single-trait models for some colorimetric traits in pepper. While model validation performs poorly on wild tomato accessions, the usage as many as one accession per wild species in the training set can increase the transferability of models to unseen populations for some traits (e.g. fruit shape for which predictability in unseen scenario increased from zero to 0.6). Overall, GS approaches can assist the selection of high-performance Solanaceous fruits in crop breeding.
Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems, likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost-vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost multilayer forest land-surface model (CryoGrid) with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain. <br /> Following parameterization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions covering a gradient of summergreen forests in the east at Spasskaya Pad, mixed summergreen-evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the southeast of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active layer thickness (ALT) and soil moisture, and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of eastern Siberia by reproducing vegetation patterns, making it an excellent tool to disentangle processes driving boreal forest dynamics.
The emergence of carbapenemase-producing multi-drug resistant Enterobacteriaceae poses a dramatic, world-wide health risk. Limited treatment options and a lack of easy-to-use methods for the detection of infections with multi-drug resistant bacteria leave the health-care system with a fast-growing challenge. Aptamers are single stranded DNA or RNA molecules that bind to their targets with high affinity and specificity and can therefore serve as outstanding detection probes. However, an effective aptamer selection process is often hampered by non-specific binding. When selections are carried out against recombinant proteins, purification tags (e.g. polyhistidine) serve as attractive side targets, which may impede protein target binding. In this study, aptamer selection was carried out against N-terminally hexa-histidine tagged New Delhi metallo-ss-lactamase 1. After 14 selection rounds binding to polyhistidine was detected rather than to New Delhi metallo-ss-lactamase 1. Hence, the selection strategy was changed. As one aptamer candidate showed remarkable binding affinity to polyhistidine, it was used as a masking probe and selection was restarted from selection round 10. Finally, after three consecutive selection rounds, an aptamer with specific binding properties to New Delhi metallo-ss-lactamase 1 was identified. This aptamer may serve as a much-needed detection probe for New Delhi metallo-ss-lactamase 1 expressing Enterobacteriaceae.
In an ocean-continent subduction zone, the assessment of the lithospheric thermal state is essential to determine the controls of the deformation within the upper plate and the dip angle of the subducting lithosphere. In this study, we evaluate the degree of influence of both the configuration of the upper plate (i.e., thickness and composition of the rock units) and variations of the subduction angle on the lithospheric thermal field of the southern Central Andes (29 degrees-39 degrees S). Here, the subduction angle increases from subhorizontal (5 degrees) north of 33 degrees S to steep (similar to 30 degrees) in the south. We derived the 3D temperature and heat flow distribution of the lithosphere in the southern Central Andes considering conversion of S wave tomography to temperatures together with steady-state conductive thermal modeling. We found that the orogen is overall warmer than the forearc and the foreland and that the lithosphere of the northern part of the foreland appears colder than its southern counterpart. Sedimentary blanketing and the thickness of the radiogenic crust exert the main control on the shallow thermal field (<50km depth). Specific conditions are present where the oceanic slab is relatively shallow (<85 km depth) and the radiogenic crust is thin. This configuration results in relatively colder temperatures compared to regions where the radiogenic crust is thick and the slab is steep. At depths >50km, the temperatures of the overriding plate are mainly controlled by the mantle heat input and the subduction angle. The thermal field of the upper plate likely preserves the flat subduction angle and influences the spatial distribution of shortening.
Background:
Corona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens need to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app uptake is crucial.
Objective:
This study aimed to add to our understanding of underlying psychological factors motivating app uptake. More specifically, we investigated the role of concern for one's own health and concern to unknowingly infect others.
Methods:
A two-wave survey with 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments (Corona-Warn-App, Germany; SwissCovid, Switzerland), as well as concerns regarding COVID-19 and control variables.
Results:
Controlling for demographic variables and general attitudes toward the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (odds ratio [OR] 1.64, P=.002). Meanwhile, concern of unknowingly infecting others did not contribute significantly to the prediction of app uptake over and above concern for one's own health (OR 1.01, P=.92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app uptake provokes changes in levels of concern. Testing for a curvilinear relationship, there was no evidence that "too much" concern leads to defensive reactions and reduces app uptake.
Conclusions:
As one of the first studies to assess the installation of already launched corona tracing apps, this study extends our knowledge of the motivational landscape of app uptake. Based on this, practical implications for communication strategies and app design are discussed.
Background
Secondary endosymbionts of aphids provide benefits to their hosts, but also impose costs such as reduced lifespan and reproductive output. The aphid Aphis fabae is host to different strains of the secondary endosymbiont Hamiltonella defensa, which encode different putative toxins. These strains have very different phenotypes: They reach different densities in the host, and the costs and benefits (protection against parasitoid wasps) they confer to the host vary strongly.
Results
We used RNA-Seq to generate hypotheses on why four of these strains inflict such different costs to A. fabae. We found different H. defensa strains to cause strain-specific changes in aphid gene expression, but little effect of H. defensa on gene expression of the primary endosymbiont, Buchnera aphidicola. The highly costly and over-replicating H. defensa strain H85 was associated with strongly reduced aphid expression of hemocytin, a marker of hemocytes in Drosophila. The closely related strain H15 was associated with downregulation of ubiquitin-related modifier 1, which is related to nutrient-sensing and oxidative stress in other organisms. Strain H402 was associated with strong differential regulation of a set of hypothetical proteins, the majority of which were only differentially regulated in presence of H402.
Conclusions
Overall, our results suggest that costs of different strains of H. defensa are likely caused by different mechanisms, and that these costs are imposed by interacting with the host rather than the host's obligatory endosymbiont B. aphidicola.
Both ice sheets in Greenland and Antarctica are discharging ice into the ocean. In many regions along the coast of the ice sheets, the icebergs calve into a bay. If the addition of icebergs through calving is faster than their transport out of the embayment, the icebergs will be frozen into a melange with surrounding sea ice in winter. In this case, the buttressing effect of the ice melange can be considerably stronger than any buttressing by mere sea ice would be. This in turn stabilizes the glacier terminus and leads to a reduction in calving rates. Here we propose a simple parametrization of ice melange buttressing which leads to an upper bound on calving rates and can be used in numerical and analytical modelling.
Klossowski, who had originally started as a religious seeker of truth in his younger years, will – after his « reversal » – feel himself invested with the role of a « heretic » struggling with the libidinous search for truth. Even as the creator of a perverted metaphysics, he remains a seeker of the revelation of being, now in the role of the divine « adversary » who, thrown back on himself, tends to imitate a religious mystic. The divine is replaced by the whispers of the demon, which Klossowski experiences as « la complicité d'une force "démonique" » in the creation of his artworks. The Diana myth becomes a parable for the act of artistic creation. Sexuality, understood as the primordial ground of creative force that shapes the signe unique, the phantasm, shifts metaphysics to « phantasmaphysics » (Foucault), in which the mystery of the divine is exposed as a delusion (Wahnbild).