Abstract: Dysregulation of miRNA expression occurs in many cancers, making miRNAs useful in cancer diagnosis and therapeutic guidance. In a clinical context using methods such as polymerase chain reaction (PCR), the limited amount of miRNAs in circulation often limits their quantification. Here, we present a PCR-free and sensitive singlet oxygen (1O2)-based strategy for the detection and quantification of miRNAs in untreated human plasma from patients diagnosed with prostate cancer. A target miRNA is specifically captured by functionalised magnetic beads and a detection oligonucleotide probe in a sandwich-like format. The formed complex is concentrated at the sensor surface via magnetic beads, providing an interface for the photoinduced redox signal amplification. The detection oligonucleotide probe bears a molecular photosensitiser, which produces 1O2 upon illumination, oxidising a redox reporter and creating a redox cycling loop, allowing quantification of pM level miRNA in diluted human plasma within minutes after hybridisation and without target amplification.

Abstract: Climate change impact, food security concerns, and greenhouse gas emissions are pressuring agricultural production systems in developing countries. There is a need for a shift toward sustainable food systems. One of the concepts introduced to drive this shift is climate-smart agriculture (CSA), endorsed by international organizations to address multifaceted challenges. Despite widespread attention and support, the adoption of CSA among African farmers remains low. This systematic literature review aims to shed light on the factors influencing CSA adoption amongst African farmers. Within the articles identified as relevant, over 50 CSA practices and more than 40 factors influencing CSA adoption were distinguished. These influencing factors can be categorized as personal, farm- related, financial, environmental, and informational. The focus of this review is to identify and explain the overall impact (positive, negative, or mixed) of these factors on CSA adoption. Overall, many factors result in mixed effects, only some factors have an unambiguous positive or negative effect on CSA adoption. For instance, educational level emerges as a key personal factor, positively impacting CSA adoption, along with positive influences from farmers’ experience and farm size among farm-related factors. Financial factors reveal distinct patterns, with income from farming and access to credit positively influencing adoption, while off-farm income exhibits a negative effect. Environmental factors, though less researched, indicate positive impacts related to changes in rainfall patterns, temperature, and droughts. Lastly, informational factors consistently exhibit a positive effect on CSA adoption, with training, access to extension, group memberships, climate information, and CSA awareness playing crucial roles. These findings provide valuable insights for policymakers seeking to enhance CSA adoption in Africa, offering a nuanced understanding of the multifaceted dynamics at play.

Abstract: Incorporating natural spaces within urban areas has been shown to have multiple benefits. However, despite greening and adaptation strategies at different levels of government, progress remains slow with a lack of easy to use and comprehensive tools identified as key to overcoming this. This paper presents a co-designed tool with academic and local authority partners to demonstrate the ecosystem service benefits of small-scale urban green infrastructure projects. Through the tool, users can readily assess the impact of green infrastructure investments on the delivery of a selection of ecosystem services in the early stages of a project. Furthermore, the tool provides a standardised assessment of cultural ecosystem services' contributions, as well as offering a method to score spatial designs on the impact on habitat for biodiversity. Use of the tool is demonstrated using a pilot study in Kapelle, the Netherlands. The results set out an overview of the impacts of the spatial design on estimated ecosystem service delivery. They also show the tool's potential to add value in early project stages and as a planning and design tool, helping to maximise the benefits that can be achieved through green infrastructure design. Complementing these arguments with ball-park estimations on green infrastructure costs, the Nature Smart Cities Business Model aims to offer public sector officers the means to create a business case for green infrastructure measures, facilitating the translation from strategies to actual plans, thus benefitting green infrastructure implementation in the public realm.

Abstract: Appropriate use of agricultural technologies and diversifying the farming activities is critical to addressing food security problems in Africa, including Ethiopia. The country is experimenting with the new Agricultural Innovation System (AIS) approach alongside the well-established Transfer of Technology (ToT) approach. This paper analyzes the gaps between policy discourses (as reflected in policy documents and strategic orientation documents) and extension practices (as reflected in the daily exchanges between farmers and the frontline staff of the Ethiopian extension system). It provides insights into the challenges faced and emphasizes the need for better coordination between policy formulation and implementation to enhance extension services. Policymakers, practitioners, and researchers can benefit from the valuable perspectives the findings offer. The study contributes to understanding the relationship between policy discourses and extension practices, and its implications can inform policy design and implementation in similar contexts. A qualitative research approach was deployed to analyze policy discourse and practice. Data were collected in Fogera, a district in Northwest Ethiopia, between August 2018 and February 2019. The data for the paper were obtained from 23 Focus Group Discussions conducted with men and women. 13 Informant Interviews (KIIs) were also carried out with personnel at different levels of government agricultural services and departments. Transcripts of recordings of the Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs) were analyzed using a deductive approach. The study focuses on rice crops in the Fogera district, which are crucial for food security and reducing poverty. Although the geographic area is limited, the results can be used to improve the extension system in other areas facing similar challenges. Specifically, the study suggests switching from the traditional transfer of technology approach to the agricultural innovation system approach. Furthermore, the study's techniques, such as qualitative interviews, may have limitations and not fully capture the intricacies of policy and extension practices. The findings demonstrate that, although the policy documents strongly adhere to agricultural innovation system principles, top-down transfer of technology approaches continues to dominate in practice. Moreover, we have found potential discrepancies between the training content delivered and the specific needs of smallholder farmers. Practically, prescriptive systems are still used because agricultural innovation system approaches are not well understood by the Extension Agents. To realize a genuine agricultural innovation system, Ethiopia's extension apparatus should move forward with building committed and robust relationships between farmers, extension agents, researchers, private sectors, and non-governmental organizations. To this end, more research, enhanced training, and improved institutions are needed on what genuine agricultural innovation system could look like at the grass-roots level. This also includes understanding the roles that different actors within Ethiopia's development army should assume how a multi-actor policy dialogue can be organized.

Abstract: Climate change is causing alterations in precipitation patterns, leading to adverse ecological consequences in many ecosystems. Recently, an increasingly persistent weather pattern has emerged, characterized by lengthening the duration of alternating dry and wet periods, which is more complex than exclusively drought or increasing precipitation. It is currently unclear how soil microbial communities respond to these new regimes in relation to their interactions with plants, especially in precipitation-sensitive ecosystems, such as tropical rainforests and grasslands. In this thesis, we explored responses of soil bacterial and fungal communities to increasing weather persistence in rainforests and grasslands, using high throughput sequencing technology. We firstly investigated the resistance and resilience of microbial communities to prolonged drought in a mature seasonal tropical rainforest which experiences unusually intensive dry seasons in the current century. Through excluding rainfall during and after the dry season, a simulated prolongation of the dry season by five months was compared to the control. Our results indicate that as rain exclusion progressed, the microbial communities increasingly diverged from the control, indicating a moderate resistance to prolonged drought. However, when the drought ceased, the composition and co-occurrence patterns of soil microbial communities immediately recovered to that in the control, implying a high resilience. To further investigate the ecological roles of soil microbial communities in response to increasing weather persistence, we set up grassland mesocosm experiments. In these experiments, precipitation frequency was adjusted along a series, ranging from 1 to 60 consecutive days alternating of dry and wet periods, while keeping the total precipitation constant. Our results show that microbial community assembly tended to be more stochastic processes at intermediate persistence of dry and wet alternations while more deterministic processes dominated at low and high persistence within 120 days regime exposure. Moreover, more persistent precipitation reduced the fungal diversity and network connectivity but barely impacted that of bacterial communities. The prior experiences of persistent weather events for one year caused legacy effects. The soil microbial legacy induced by soil microbial communities subjected to prior persistent weather events was more enduring in subsequent fungal communities than bacterial communities, likely due to slower growth of fungi compared to bacteria. However, a minor effect of soil microbial legacy  was observed on plant performance. In addition, we kept the grassland mesocosm experiment for two growing seasons. The effects of precipitation persistence on soil microbial communities increased in the second year. The dissimilarities of microbial communities between the first and second year were less with more persistent precipitation, potentially resulting in more vulnerable microbial communities, due to some taxa disappearing and a reduction in functional redundancy under more persistent weather. To conclude, our findings provide a comprehensive theoretical understanding of soil microbial communities in response to the current and future climate change, drawing from both natural and experimental systems. It helps in predicting and managing the impacts of future climate change on ecosystems mediated by microbial communities. Additionally, the findings of microbe-mediated legacy effects on grassland ecosystems can provide practical guidance for their application in agriculture, specifically for using an inoculum to mitigate the impacts of climate change.

Abstract: Accurate segmentation of nanoparticles within various matrix materials is a difficult problem in electron tomography. Due to artifacts related to image series acquisition and reconstruction, global thresholding of reconstructions computed by established algorithms, such as weighted backprojection or SIRT, may result in unreliable and subjective segmentations. In this paper, we introduce the Partially Discrete Algebraic Reconstruction Technique (PDART) for computing accurate segmentations of dense nanoparticles of constant composition. The particles are segmented directly by the reconstruction algorithm, while the surrounding regions are reconstructed using continuously varying gray levels. As no properties are assumed for the other compositions of the sample, the technique can be applied to any sample where dense nanoparticles must be segmented, regardless of the surrounding compositions. For both experimental and simulated data, it is shown that PDART yields significantly more accurate segmentations than those obtained by optimal global thresholding of the SIRT reconstruction.

Abstract: The concept of resolution in high-resolution electron microscopy (HREM) is the power to resolve neighboring atoms. Since the resolution is related to the width of the point spread function of the microscope, it could in principle be determined from the image of a point object. However, in electron microscopy there are no ideal point objects. The smallest object is an individual atom. If the width of an atom is much smaller than the resolution of the microscope, this atom can still be considered as a point object. As the resolution of the microscope enters the sub-Å regime, information about the microscope is strongly entangled with the information about the atoms in HREM images. Therefore, we need to find an alternative method to determine the resolution in an object-independent way. In this work we propose to use the image wave of a crystalline object in zone axis orientation. Under this condition, the atoms of a column act as small lenses so that the electron beam channels through the atom column periodically. Because of this focusing, the image wave of the column can be much more peaked than the constituting atoms and can thus be a much more sensitive probe to measure the resolution. Our approach is to use the peakiness of the image wave of the atom column to determine the resolution. We will show that the resolution can be directly linked to the total curvature of the atom column wave. Moreover, we can then directly obtain the resolution of the microscope given that the contribution from the object is known, which is related to the bounding energy of the atom. The method is applied on an experimental CaTiO3 image wave.

Abstract: In the present paper, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. In order to count the number of atoms, it is assumed that the total scattered intensity scales with the number of atoms per atom column. These intensities are quantitatively determined using model-based statistical parameter estimation theory. The distribution describing the probability that intensity values are generated by atomic columns containing a specific number of atoms is inferred on the basis of the experimental scattered intensities. Finally, the number of atoms per atom column is quantified using this estimated probability distribution. The number of atom columns available in the observed STEM image, the number of components in the estimated probability distribution, the width of the components of the probability distribution, and the typical shape of a criterion to assess the number of components in the probability distribution directly affect the accuracy and precision with which the number of atoms in a particular atom column can be estimated. It is shown that single atom sensitivity is feasible taking the latter aspects into consideration.

Abstract: Atomically resolved electron energy-loss spectroscopy experiments are commonplace in modern aberration-corrected transmission electron microscopes. Energy resolution has also been increasing steadily with the continuous improvement of electron monochromators. Electronic excitations however are known to be delocalized due to the long range interaction of the charged accelerated electrons with the electrons in a sample. This has made several scientists question the value of combined high spatial and energy resolution for mapping interband transitions and possibly phonon excitation in crystals. In this paper we demonstrate experimentally that atomic resolution information is indeed available at very low energy losses around 100 meV expressed as a modulation of the broadening of the zero loss peak. Careful data analysis allows us to get a glimpse of what are likely phonon excitations with both an energy loss and gain part. These experiments confirm recent theoretical predictions on the strong localization of phonon excitations as opposed to electronic excitations and show that a combination of atomic resolution and recent developments in increased energy resolution will offer great benefit for mapping phonon modes in real space.

Abstract: We demonstrate the production of an ordered array of electron vortices making use of an electron optical setup consisting of two electrostatic biprisms. The biprism filaments are oriented nearly orthogonal with respect to each other in a transmission electron microscope. Matching the position of the filaments, we can choose to form different topological features in the electron wave. We outline the working principle of the setup and demonstrate fist experimental results. This setup partially bridges the gap between angular momentum carried by electron spin, which is intrinsic and therefore present in any position of the wave, and angular momentum carried by the vortex character of the wave, which can be extrinsic depending on the axis around which it is measured. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: Dark-held electron holography maps strain in crystal lattices into reconstructed phases over large fields of view. Here we investigate the details of the lattice strain-reconstructed phase relationship by applying dynamic scattering theory both analytically and numerically. We develop efficient analytic linear projection rules for 3D strain fields, facilitating a straight-forward calculation of reconstructed phases from 3D strained materials. They are used in the following to quantify the influence of various experimental parameters like strain magnitude, specimen thickness, excitation error and surface relaxation. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: Quantitative structural and chemical information can be obtained from high angle annular dark field scanning transmission electron microscopy (HAADF STEM) images when using statistical parameter estimation theory. In this approach, we assume an empirical parameterized imaging model for which the total scattered intensities of the atomic columns are estimated. These intensities can be related to the material structure or composition. Since the experimental probe profile is assumed to be known in the description of the imaging model, we will explore how the uncertainties in the probe profile affect the estimation of the total scattered intensities. Using multislice image simulations, we analyze this effect for Cs corrected and non-Cs corrected microscopes as a function of inaccuracies in cylindrically symmetric aberrations, such as defocus and spherical aberration of third and fifth order, and non-cylindrically symmetric aberrations, such as 2-fold and 3-fold astigmatism and coma.