Finding Rare Quasars: VLA Snapshot Continuum Survey of FRI Quasar Candidates Selected from the LOFAR Two-Metre Sky Survey (LoTSS)

The radiative and jet power in active galactic nuclei is generated by accretion of material on to supermassive galactic-centre black holes. For quasars, where the radiative power is by definition very high, objects with high radio luminosities form ∼10 per cent of the population, although it is not clear whether this is a stable phase. Traditionally, quasars with high radio luminosities have been thought to present jets with edge-brightened morphology (Fanaroff-Riley II−FR II) due to the limitations of previous radio surveys (i.e., FRIs were not observed as part of the quasar population). The LOw Frequency ARray (LOFAR) Two-metre Sky Survey (LoTSS) with its unprecedented sensitivity and resolution covering wide sky areas has enabled the first systematic selection and investigation of quasars with core-brightened morphology (Fanaroff-Riley I−FR). We carried out a Very Large Array (VLA) snapshot survey to reveal inner structures of jets in selected quasar candidates; 15 (25 per cent) out of 60 sources show clear inner jet structures that are diagnostic of FRI jets and 13 quasars (∼22 per cent) show extended structures similar to those of FRI jets. Black hole masses and Eddington ratios do not show a clear difference between FRI and FRII quasars. FRII quasars tend to have higher jet powers than FRI quasars. Our results show that the occurrence of FRI jets in powerful radiatively efficient systems is not common, probably mainly due to two factors: galaxy environment and jet power.

Credible Mendelian Randomization Studies in the Presence of Selection Bias Using Control Exposures

Selection bias is increasingly acknowledged as a limitation of Mendelian randomization (MR). However, few methods exist to assess this issue. We focus on two plausible causal structures relevant to MR studies and illustrate the data-generating process underlying selection bias via simulation studies. We conceptualize the use of control exposures to validate MR estimates derived from selected samples by detecting potential selection bias and reproducing the exposure–outcome association of primary interest based on subject matter knowledge. We discuss the criteria for choosing the control exposures. We apply the proposal in an MR study investigating the potential effect of higher transferrin with stroke (including ischemic and cardioembolic stroke) using transferrin saturation and iron status as control exposures. Theoretically, selection bias affects associations of genetic instruments with the outcome in selected samples, violating the exclusion-restriction assumption and distorting MR estimates. Our applied example showing inconsistent effects of genetically predicted higher transferrin and higher transferrin saturation on stroke suggests the potential selection bias. Furthermore, the expected associations of genetically predicted higher iron status on stroke and longevity indicate no systematic selection bias. The routine use of control exposures in MR studies provides a valuable tool to validate estimated causal effects. Like the applied example, an antagonist, decoy, or exposure with similar biological activity as the exposure of primary interest, which has the same potential selection bias sources as the exposure–outcome association, is suggested as the control exposure. An additional or a validated control exposure with a well-established association with the outcome is also recommended to explore possible systematic selection bias.

Identification of the Most Suitable App to Support the Self-Management of Hypertension: Systematic Selection Approach and Qualitative Study

Background Smartphone apps are increasingly being used to aid in hypertension self-management, and a large and ever-growing number of self-management apps have been commercially released. However, very few of these are potentially effective and secure, and researchers have yet to establish the suitability of specific hypertension apps to particular contexts. Objective The aim of this study is to identify the most suitable hypertension app in the context of Saudi Arabia and its health system. Methods This study used a 2-stage approach to selecting the most suitable app for hypertension self-management. First, a systematic selection approach was followed to identify a shortlist of the most suitable apps according to the criteria of potential effectiveness, theoretical underpinning, and privacy and security. Second, an exploratory qualitative study was conducted to select the most suitable from the shortlist: 12 doctors were interviewed, and 22 patients participated in 4 focus groups. These explored participants’ attitudes towards self-management apps in general, and their views towards the apps identified via the systematic selection process. The qualitative data were analyzed using framework analysis. Results In the first stage, only 5 apps were found to be potentially effective while also having a theoretical underpinning and protecting users’ data. In the second stage, both doctors and patients were generally interested in using hypertension apps, but most had no experience with these apps due to a lack of awareness of their availability and suitability. Patients and doctors liked apps that combine intuitive interfaces with a pleasant and clear visual design, in-depth features (eg, color-coded feedback accompanied with textual explanations), activity-specific reminders, and educational content regarding hypertension and potential complications. When the pros and cons of the 5 apps were discussed, 3 apps were identified as being more suitable, with Cora Health rated the highest by the participants. Conclusions Only 5 apps were deemed potentially effective and secure. Patients’ and doctors’ discussions of the pros and cons of these 5 apps revealed that 3 out of the 5 are clearly more suitable, with the Cora Health app being judged most suitable overall.

Drought-adapted maize line based on morphophysiological selection index

Padjung R, Farid M, Musa Y, Anshori MF, Nur A, Masnenong A. 2021. Drought-adapted maize line based on morphophysiological selection index. Biodiversitas 22: 4028-4035. Synthetic line formation is an effort to increase maize productivity in drought-stressed areas. This process requires systematic selection in determining adaptability levels involving important secondary characters formulated in the selection index. Furthermore, the principal component index had been widely reported, both in normal and stressed conditions. The selection index development on morpho-physiological characters based on multivariate analysis was expected to increase drought stress tolerance and maize lines selection precision. Therefore, the purpose of this research was to form a selection index based on morpho-physiological characters and selecting synthetic lines adaptive under drought stress. This research was designed using a split-plot with 3 replications, where the main plot consisted of normal and stressed irrigation, while the subplot was genotype consisting of 6 lines and 3 check varieties namely Bisma, Lamuru, and Sukamarga. Observations were performed on 18 morphological and 4 physiological characters, and the results showed that the selection index was formed based on multivariate analysis from 9 characters. Through index selection, Syn_2-2 (0.79), Syn_2-15 (0.85) and Syn_2-16 (0.97) were considered as drought stress adaptive lines. Therefore, the 3 lines can be recommended in the synthetic variety release process.

COVID-19 in Liver Transplant Recipients: A Systematic Review

Liver transplant (LT) recipients are considered a vulnerable population amidst the COVID-19 pandemic. To date, available data have been heterogeneous and scarce. Therefore, we conducted a systematic literature review identifying English-language articles published in PubMed between November 2019 and 30th May 2021. We aimed to explore three areas: (1) outcome and clinical course; (2) immunological response after COVID-19 in LT recipients; and (3) vaccination response. After systematic selection, 35, 4, and 5 articles, respectively, were considered suitable for each area of analysis. Despite the heterogeneity of the reports included in this study, we found that gastrointestinal symptoms were common in LT recipients. The outcome of the LT population was not per se worse compared to the general population, although careful management of immunosuppressive therapy is required. While a complete therapy discontinuation is not encouraged, caution needs to be taken with use of mycophenolate mofetil (MMF), favoring tacrolimus (TAC) use. Although data conflicted about acquired immunity after SARS-CoV-2 infection, vaccine immunogenicity appeared to be low, suggesting that the level of surveillance should be kept high in this population.

Global access to COVID-19 vaccines: a scoping review of factors that may influence equitable access for low and middle-income countries

ObjectiveTo identify the factors contributing to equitable access to COVID-19 vaccines for low and middle-income countries (LMIC).MethodsWe conducted a scoping review following the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews and a five-stage framework for scoping studies. We performed systematic searches for published peer-reviewed literature in five databases: Medline, Embase, Web of Science, Global Index Medicus and COVID-19 Evidence Epistemonikos (August 2020, updated May 2021).ResultsSystematic selection according to predefined criteria resulted in the final inclusion of 45 peer-reviewed articles, with no limitations on study design or publication type. We derived four key factors that potentially influence equitable access to COVID-19 vaccines in LMICs: (1) collectively agreed global mechanisms or frameworks; (2) bilateral purchasing, contracting, and vaccine prices; (3) vaccine manufacturing that is supported by sharing know-how; and (4) countries’ strength in implementing vaccination programmes.ConclusionsThis scoping review highlights the ongoing challenges for the international community in ensuring equitable access to COVID-19 vaccines for LMICs. The literature suggests that vaccine manufacturing can influence the supply of vaccines, as can the role of patent holders who can influence global governance through their role in the distribution of COVID-19 vaccines. Our findings indicate that including the principles of equitable access throughout vaccine research and development, procurement, scale-up and distribution processes can support equitable access for LMICs. Advances made with mRNA vaccines may have additional benefits in relation to expanding the manufacturing of other vaccine. Finally, the exploration and scale-up of such capacities of LMICs are likely to prove to be a valuable investment, even after the pandemic.

Optimization of Spiral-Wound Microfiltration Process Parameters for the Production of Micellar Casein Concentrate

A systematic selection of different transmembrane pressures (TMP) and levels of diafiltration (DF) was studied to optimize these critical process parameters during the manufacturing of micellar casein concentrate (MCC) using spiral-wound polymeric membrane filtration. Three TMPs (34.5, 62.1, and 103.4 kPa) and four DF levels (0, 70, 100, and 150%) were applied in the study. The effect of the TMP and DF level on flux rates, serum protein (SP) removal, the casein-to-total-protein ratio, the casein-to-true-protein ratio, and the rejection of casein and SP were evaluated. At all transmembrane pressures, the overall flux increased with increases in the DF level. The impact of DF on the overall flux was more pronounced at lower pressures than at higher pressures. With controlled DF, the instantaneous flux was maintained within 80% of the initial flux for the entire process run. The combination of 34.5 kPa and a DF level of 150% resulted in 81.45% SP removal, and a casein-to-true-protein ratio of 0.96. SP removal data from the lab-scale experiments were fitted into a mathematical model using DF levels and the square of TMPs as factors. The model developed in this study could predict SP removal within 90–95% of actual SP removal achieved from the pilot plant experiments.

Systematic selection of competing metabolomics methods in a metabolite-sensory relationship study

Introduction The relationship between the chemical composition of food products and their sensory profile is a complex association confronting many challenges. However, new untargeted methodologies are helping correlate metabolites with sensory characteristics in a simpler manner. Nevertheless, in the pilot phase of a project, where only a small set of products are used to explore the relationships, choices have to be made about the most appropriate untargeted metabolomics methodology. Objective To provide a framework for selecting a metabolite-sensory methodology based on: the quality of measurements, the relevance of the detected metabolites in terms of distinguishing between products or in terms of whether they can be related to the sensory attributes of the products. Methods In this paper we introduce a systematic approach to explore all these different aspects driving the choice for the most appropriate metabolomics method. Results As an example we have used a tomato soup project where the choice between two sampling methods (SPME and SBSE) had to be made. The results are not always consistently pointing to the same method as being the best. SPME was able to detect metabolites with a better precision, SBSE seemed to be able to provide a better distinction between the soups. Conclusion The three levels of comparison provide information on how the methods could perform in a follow up study and will help the researcher to make a final selection for the most appropriate method based on their strengths and weaknesses.

Optimization of a clamping concept based on machine learning

Fixtures are an important element of the manufacturing system, as they ensure productive and accurate machining of differently shaped workpieces. Regarding the fixture design or the layout of fixture elements, a high static and dynamic stiffness of fixtures is therefore required to ensure the defined position and orientation of workpieces under process loads, e.g. cutting forces. Nowadays, with the increase in computing performance and the development of new algorithms, machine learning (ML) offers an appropriate possibility to use regression methods for creating realistic, rapid and reliable equivalent ML models instead of simulations based on the finite element method (FEM). This research work introduces a novel method that allows an optimization of clamping concepts and fixture design by means of ML, in order to reduce manufacturing errors and to obtain an increased stiffness of fixtures and machining accuracy. This paper describes the preparation of a dataset for training ML models, the systematic selection of the most promising regression algorithm based on relevant criteria, the implementation of the chosen algorithm Extreme Gradient Boosting (XGBoost) and other comparable algorithms, the analysis of their regression results, and the validation of the optimization for a selected clamping concept.

Securing genetic integrity in freshwater pearl mussel propagation and captive breeding

Securing genetic integrity is of key importance in conservation-oriented captive breeding programs releasing juveniles into the wild. This is particularly true for species such as the endangered freshwater pearl mussel (Margaritifera margaritifera) for which a number of captive breeding facilities has been established in Europe. The core objective of this study was to compare the genetic constitution of 29 cohorts of captive-bred freshwater pearl mussels from five different breeding facilities in Austria, France, Luxembourg and Germany, with their original 14 source populations from nine major European drainages, based on microsatellite markers. Captive-bred mussels represented 11 different genetic clusters, suggesting an important contribution of the breeding stations to securing the genetic diversity of the species. In almost all cases, the cultured offspring closely resembled the genetic constitution of the source mussels as revealed from the STRUCTURE analysis and the generally high assignment of offspring to the original source populations. The majority of captive-bred cohorts had an increased inbreeding coefficient and decreased genetic variability compared to their source populations as measured by AR and HO. Highest numbers of deformed juveniles coincided with very low levels of HO < 0.05. Since erosion of genetic diversity in captive breeding was mostly evident in individual year-cohorts, long-term breeding over multiple years can minimize such effects. The systematic selection of priority populations for conservation, effective breeding strategies avoiding effects of in- and outbreeding by genetically informed selection of parent individuals, and a network of collaboration among the different breeding facilities would be very useful to increase resilience and effectiveness.