Kusktolstrup8970

Tissue microarrays (TMAs) are commonly used for the rapid analysis of large numbers of tissue samples, often in morphological assessments but increasingly in spectroscopic analysis, where specific molecular markers are targeted via immunostaining. Here we report the use of an automated high-throughput system based on desorption electrospray ionization (DESI) mass spectrometry (MS) for the rapid generation and online analysis of high-density (6144 samples/array) TMAs, at rates better than 1 sample/second. Direct open-air analysis of tissue samples (hundreds of nanograms) not subjected to prior preparation, plus the ability to provide molecular characterization by tandem mass spectrometry (MS/MS), make this experiment versatile and applicable to both targeted and untargeted analysis in a label-free manner. These capabilities are demonstrated in a proof-of-concept study of frozen brain tissue biopsies where we showcase (i) a targeted MS/MS application aimed at identification of isocitrate dehydrogenase mutation in glioma samples and (ii) an untargeted MS tissue type classification using lipid profiles and correlation with tumor cell percentage estimates from histopathology. The small sample sizes and large sample numbers accessible with this methodology make for a powerful analytical system that facilitates the identification of molecular markers for later use in intraoperative applications to guide precision surgeries and ultimately improve patient outcomes.The lack of safe drinking water affects communities in low-to-medium-income countries most. This barrier can be overcome by using sustainable point-of-use water treatments. Solar energy has been used to disinfect water for decades, and several efforts have been made to optimise the standard procedure of solar water disinfection (SODIS process). However, the Health Impact Assessment of implementing advanced technologies in the field is also a critical step in evaluating the success of the optimisation. This work reports a sustainable scaling-up of SODIS from standard 2 L bottles to 25 L transparent jerrycans (TJC) and a 12-month field implementation in four sites of Tigray in Ethiopia, where 80.5% of the population lives without reliable access to safe drinking water and whose initial baseline average rate of diarrhoeal disease in children under 5 years was 13.5%. The UVA dose required for 3-log reduction of E. coli was always lower than the minimum UVA daily dose received in Tigray (9411 ± 55 Wh/m2). Results confirmed a similar decrease in cases of diarrhoea in children in the implementation (25 L PET TJC) and control (2 L PET bottles) groups, supporting the feasibility of increasing the volume of the SODIS water containers to produce safer drinking water with a sustainable and user-friendly process.This paper aims to explore the response of a floating icesheet to a load moving in a curved path. We investigate the effect of turning on the wave patterns and strain distribution, and explore scenarios where turning increases the wave amplitude and strain in the ice, possibly leading to crack formation, fracturing and eventual ice failure. The mathematical model used here is the linearized system of differential equations introduced in Dinvay et al. (J. Fluid Mech. 876122-149, 2019). The equations are solved using the Fourier transform in space, and the Laplace transform in time. The model is tested against existing results for comparison, and several cases of load trajectories involving turning and decelerating are tested.Number of children is an important human trait and studies have indicated associations with single-nucleotide polymorphisms (SNPs). Aim to give further evidence for four associations using a large sample of Polish subjects. Data from the POPULOUS genetic database was provided from anonymous, healthy, unrelated, Polish volunteers of both sexes (N = 5760). SNPs (n = 173) studied (a) 69 from the chromosome 17 H1/H2 inversion; (b) six from 1q21.3, 5q21.3 and 14q21.2; and (c) 98 random negative controls. Zero-inflated negative-binomial regression (z.i.) was performed (0-3 numbers of children per individual (NCI) set as non-events; adjustors year of birth, sex). Significance level p = 0.05 with Bonferroni correction. Statistically-significant differences (with data from both sexes combined) were obtained from highly-linked inversion SNPs representative rs12373123 gave means homozygotes TT 2.31 NCI (n = 1418); heterozygotes CT 2.35 NCI (n = 554); homozygotes CC 2.44 NCI (n = 43) (genotype p = 0.01; TTvs.CC p = 0.004; CTvs.CC p = 0.009). (Male data alone gave similar results.) Recessive modeling indicated that H2-homozygotes had 0.118 more children than H1-homozygotes + heterozygotes (z.i.-count estimates ± standard errors CT, - 0.508 ± 0.194; TT, - 0.557 ± 0.191). The non-over-dispersed count model detected no interactions of importance there was no significant interaction with age. No positive results were obtained from negative-control SNPs or (b). Conclusions association between the H1/H2 inversion and numbers of children (previously reported in Iceland) has been confirmed, albeit using a different statistical model. One limitation is the small amount of data, despite initially ~ 6000 subjects. Causal studies require further investigation.Intelligent and coordinated unmanned aerial vehicle (UAV) swarm combat will be the main mode of warfare in the future, and mechanistic design of autonomous cooperation within swarms is the key to enhancing combat effectiveness. Exploration of the essential features and patterns of autonomous collaboration in unmanned swarms has become the focus of scientific research and technological applications, in keeping with the evolving conceptions of the military theatre. However, given the unique attributes of the military and the novelty of the warfare mode of unmanned swarms, few achievements have been reported in the existing research. In this study, we analysed the military requirements of unmanned swarm operations and proposed an analytic framework for autonomous collaboration. Then, a literature review addressing swarm evolution dynamics, game-based swarm collaboration, and collaborative evolution on complex networks was conducted. Next, on the basis of the above work, we designed a community network for unmanned swarm cooperation and constructed a collaborative evolution model based on the multiplayer public goods game (PGG). Furthermore, according to the "network" and "model", the dynamic evolution process of swarm collaboration was formally deduced. Finally, a simulation was conducted to analyse the influence of relevant parameters (i.e., swarm size, degree distribution, cost, multiplication factor) on the collaborative behaviour of unmanned swarms. According to the simulation results, some reasonable suggestions for collaborative management and control in swarm operation are given, which can provide theoretical reference and decision-making support for the design of coordination mechanisms and improved combat effectiveness in unmanned swarm operation.Pine wilt disease (PWD) is a destructive vector-borne forest disease caused by the nematode Bursaphelenchus xylophilus. To date, several options are available for the management of pine wilt disease; however constant development and search for natural products with potential nematicidal activity are imperative to diversify management options and to cope with the possible future emergence of resistance in parasitic nematodes. Here, a combined metabolomics and genomics approach was employed to investigate the chemical repertoire and biosynthetic potential of the bacterial endophyte Peribacillus frigoritolerans BE93, previously characterized to exhibit nematicidal activity against B. xylophilus. Feature-based molecular networking revealed the presence of diverse secondary metabolites. A cyclic imine heptapeptide, koranimine, was found to be among the most abundant secondary metabolites produced. Genome mining displayed the presence of several putative biosynthetic gene clusters (BGCs), including a dedicated non-ribosomal peptide synthase (NRPS) BGC for koranimine. Given the non-ribosomal peptide nature of koranimine, in silico molecular docking analysis was conducted to investigate its potential nematicidal activity against the target receptor ivermectin-sensitive invertebrate α glutamate-gated chloride channel (GluCl). Results revealed the binding of koranimine at the allosteric site of the channel-the ivermectin binding site. Moreover, the ligand-receptor interactions observed were mostly shared between koranimine and ivermectin when bound to the α GluCl receptor thus, suggesting a possibly shared mechanism of potential nematicidal activity. This study highlights the efficiency of combined metabolomics and genomics approach in the identification of candidate compounds.Achieving accurate and reliable maize disease identification in complex environments is a huge challenge. This is because disease images obtained from natural environments are often in complex contexts that may contain elements similar to disease characteristics or symptoms. Chk2InhibitorII Based on cascade network and two-stage transformation learning, the new method is proposed in this paper and applied the improved method to the task of identification and classification of four maize leaf types in a complex environment. The proposed method has a cascade structure which consists of a Faster R-CNN leaf detector (denoted as LS-RCNN) and a CNN disease classifier, named CENet(Complex Environment Network). The LS-RCNN detector with an attention mechanism was used to detect maize leaves from the image, and the CENet model further classified the leaf images detected in the first stage into four categories Cercospora leaf spot, Common rust, Northern Leaf Blight, and Healthy, which allowed image features to be extracted more efficiently. The subsequent use of a two-stage transfer learning strategy to train CENet models of disease images in complex contexts allows for faster training of the models while ensuring accuracy. The experimental results show that the proposed method is used to identify four types of maize leaves with an F1-score of 99.70%, which is better than some popular CNN models and others' methods, and has a more obvious advantage in terms of training speed. The model proposed in this experiment has a positive significance for exploring other Crop variety identification and classification under complex backgrounds.This paper studies the shortest time of slowing rotation of a free dynamically asymmetric rigid body (RB), analogous to Euler's case. This body is influenced by a rotatory moment of a tiny control torque with closer coefficients but not equal, a gyrostatic moment (GM) due to the presence of three rotors, and in the presence of a modest slowing viscous friction torque. Therefore, this problem can be regarded as a semi-optimal one. The controlling optimal decelerating law for the rotation of the body is constructed. The trajectories that are quasi-stationary are examined. The obtained new results are displayed to identify the positive impact of the GM. The dimensionless form of the regulating system of motion is obtained. The functions of kinetic energy and angular momentum besides the square module are drawn for various values of the GM's projections on the body's principal axes of inertia. The effect of control torques on the body's motion is investigated in a case of small perturbation, and the achieved results are compared with the unperturbed one.