Raunhorowitz0225

It is challenging to interpret hyperspectral images in an intuitive and meaningful way, as they usually contain hundreds of dimensions. We develop a visualization tool for hyperspectral images based on neural networks, which allows a user to specify the regions of interest, select bands of interest, and obtain hyperspectral clustering results in a scatterplot generated from hyperspectral features. selleck inhibitor A cascade neural network is trained to generate an scatterplot that matches the clustering centers labeled by the user. The inferred scatterplot cannot only show the clusters of points, but also provide relationships of substances. The trained neural network can be reused for time-varying datasets without re-training. Our visualization solution can keep domain experts in the analytical loop and provide an intuitive analysis of hyperspectral images while identifying different substances, which are difficult to be realized using existing hyperspectral image analysis techniques.Image smoothing is a fundamental procedure in applications of both computer vision and graphics. The required smoothing properties can be different or even contradictive among different tasks. Nevertheless, the inherent smoothing nature of one smoothing operator is usually fixed and thus cannot meet the various requirements of different applications. In this paper, we first introduce the truncated Huber penalty function which shows strong flexibility under different parameter settings. A generalized framework is then proposed with the introduced truncated Huber penalty function. When combined with its strong flexibility, our framework is able to achieve diverse smoothing natures where contradictive smoothing behaviors can even be achieved. It can also yield the smoothing behavior that can seldom be achieved by previous methods, and superior performance is thus achieved in challenging cases. These together enable our framework capable of a range of applications and able to outperform the state-of-the-art approaches in several tasks. In addition, an efficient numerical solution is provided and its convergence is theoretically guaranteed even the optimization framework is non-convex and non-smooth. A simple yet effective approach is further proposed to reduce the computational cost of our method while maintaining its performance. The effectiveness and superior performance of our approach are validated through comprehensive experiments in a range of applications.This paper presents a comprehensive underwater visual reconstruction paradigm that comprises three procedures, i.e., the E-procedure, the R-procedure, and the H-procedure. The E-procedure enhances original underwater images based on color compensation balance and weighted image fusion, yielding restored color, sharpened edges, and global contrast. The R-procedure registers multiple enhanced underwater images by exploiting global similarity and local deformation. The H-procedure homogenizes the registered underwater images by multi-scale composition strategy, which eliminates the inhomogeneous transition and brightness difference across overlapping regions, resulting in a reconstructed wide-field underwater image with comfortable and natural visibility. The three procedures operate in a cascade where the former procedure processes underwater images in a way that facilitates the latter one. We refer to the overall three procedures as the Enhancement-Registration-Homogenization (ERH) paradigm. Comprehensive qualitative and quantitative empirical evaluations reveal that our ERH paradigm outperforms state-of-the-art visual reconstruction methods, including the AutoStitch, APAP, SPHP, APNAP, and REW.

Sleep spindle features show developmental changes during infancy and have the potential to provide an early biomarker for abnormal brain maturation. Manual identification of sleep spindles in the electroencephalogram (EEG) is time-consuming and typically requires highly-trained experts. Automated detection of sleep spindles would greatly facilitate this analysis. Research on the automatic detection of sleep spindles in infant EEG has been limited to-date.

We present a random forest-based sleep spindle detection method (Spindle-AI) to estimate the number and duration of sleep spindles in EEG collected from 141 ex-term born infants, recorded at 4 months of age. The signal on channel F4-C4 was split into a training set (81 ex-term) and a validation set (30 ex-term). An additional 30 ex-term infant EEGs (channel F4-C4 and channel F3-C3) were used as an independent test set. Fourteen features were selected for input into a random forest algorithm to estimate the number and duration of spindles and the results were compared against sleep spindles annotated by an experienced clinical physiologist.

The prediction of the number of sleep spindles in the independent test set demonstrated 93.3% to 93.9% sensitivity, 90.7% to 91.5% specificity, and 89.2% to 90.1% precision. The duration estimation of sleep spindle events in the independent test set showed a percent error of 5.7% to 7.4%.

Spindle-AI has been implemented as a web server that has the potential to assist clinicians in the fast and accurate monitoring of sleep spindles in infant EEGs.

Spindle-AI has been implemented as a web server that has the potential to assist clinicians in the fast and accurate monitoring of sleep spindles in infant EEGs.In Heliconius butterflies, wing colour pattern diversity and scale types are controlled by a few genes of large effect that regulate colour pattern switches between morphs and species across a large mimetic radiation. One of these genes, cortex, has been repeatedly associated with colour pattern evolution in butterflies. Here we carried out CRISPR knockouts in multiple Heliconius species and show that cortex is a major determinant of scale cell identity. Chromatin accessibility profiling and introgression scans identified cis-regulatory regions associated with discrete phenotypic switches. CRISPR perturbation of these regions in black hindwing genotypes recreated a yellow bar, revealing their spatially limited activity. In the H. melpomene/timareta lineage, the candidate CRE from yellow-barred phenotype morphs is interrupted by a transposable element, suggesting that cis-regulatory structural variation underlies these mimetic adaptations. Our work shows that cortex functionally controls scale colour fate and that its cis-regulatory regions control a phenotypic switch in a modular and pattern-specific fashion.Skeletal stem and progenitor cell populations are crucial for bone physiology. Characterization of these cell types remains restricted to heterogenous bulk populations with limited information on whether they are unique or overlap with previously characterized cell types. Here we show, through comprehensive functional and single-cell transcriptomic analyses, that postnatal long bones of mice contain at least two types of bone progenitors with bona fide skeletal stem cell (SSC) characteristics. An early osteochondral SSC (ocSSC) facilitates long bone growth and repair, while a second type, a perivascular SSC (pvSSC), co-emerges with long bone marrow and contributes to shape the hematopoietic stem cell niche and regenerative demand. We establish that pvSSCs, but not ocSSCs, are the origin of bone marrow adipose tissue. Lastly, we also provide insight into residual SSC heterogeneity as well as potential crosstalk between the two spatially distinct cell populations. These findings comprehensively address previously unappreciated shortcomings of SSC research.Pigs are susceptible to foot-and-mouth disease virus (FMDV), and the humoral immune response plays an essential role in protection against FMDV infection. However, little information is available about FMDV-specific mAbs derived from single B cells of pigs. This study aimed to determine the antigenic features of FMDV that are recognized by antibodies from pigs. Therefore, a panel of pig-derived mAbs against FMDV were developed using fluorescence-based single B cell antibody technology. Western blotting revealed that three of the antibodies (1C6, P2-7E and P2-8G) recognized conserved antigen epitopes on capsid protein VP2, and exhibited broad reactivity against both FMDV serotypes A and O. An alanine-substitution scanning assay and sequence conservation analysis elucidated that these porcine mAbs recognized two conserved epitopes on VP2 a linear epitope (2KKTEETTLL10) in the N terminus and a conformational epitope involving residues K63, H65, L66, F67, D68 and L81 on two β-sheets (B-sheet and C-sheet) that depended on the integrity of VP2. Random parings of heavy and light chains of the IgGs confirmed that the heavy chain is predominantly involved in binding to antigen. The light chain of porcine IgG contributes to the binding affinity toward an antigen and may function as a support platform for antibody stability. In summary, this study is the first to reveal the conserved antigenic profile of FMDV recognized by porcine B cells and provides a novel method for analysing the antibody response against FMDV in its natural hosts (i.e. pigs) at the clonal level.Four mesophilic and Gram-stain-positive strains (zg-686T/zg-691 and HY186T/HY189) isolated from Tibetan Plateau wildlife (PR China) belong to the genus Gordonia according to 16S rRNA gene and genomic sequence-based phylogenetic/genomic results. They have a DNA G+C content range of 67.4-68.3 mol% and low DNA relatedness (19.2-27.6 %) with all available genomes in the genus Gordonia. Strains zg-686T/zg-691 and HY186T/HY189 had C18  1ω9c, C18  0 10-methyl, C16  1 ω7c/C16  1ω6c and C16  0 as major cellular fatty acids. The polar lipids detected in strains zg-686T and HY186T included diphosphatidylglycerol, phosphatidylethanolamine, phosphatidyl inositol mannoside and phosphatidylinositol. The respiratory quinones comprised MK8(H2) (10.8 %) and MK9(H2) (89.2 %) for strain zg-686T, and MK6 (7.7 %), MK8(H2) (8.4 %), MK8(H4) (3.1 %) and MK9(H2) (80.8 %) for strain HY186T. Optimal growth conditions were pH 7.0, 35-37 °C and 0.5-1.5 % NaCl (w/v) for strains pair zg-686T/zg-691, and pH 7.0, 28 °C and 1.5 % (w/v) NaCl for strains pair HY186T/HY189. Based on these genotypic and phenotypic results, these four strains could be classified as two different novel species in the genus Gordonia, for which the names Gordonia jinghuaiqii sp. nov. and Gordonia zhaorongruii sp. nov. are proposed. The type strains are zg-686T (=GDMCC 1.1715T =JCM 33890T) and HY186T (=CGMCC 4.7607T =JCM 33466T), respectively.Siderophores are produced by several bacteria that utilise iron in various environments. Elucidating the structure of a specific siderophore may have valuable applications in drug development. Stenotrophomonas maltophilia, a Gram-negative bacterium that inhabits a wide range of environments and can cause pneumonia, produces siderophores. However, the structure was unknown, and therefore, in this study, we aimed to elucidate it. We purified siderophores from cultures of S. maltophilia K279a using preparative reversed-phase HPLC. The structure was analysed through LC-MS and 1H and 13C NMR. The results demonstrated that S. maltophilia K279a produces 2,3-dihydroxybenzoylserine (DHBS), a monomer unit of enterobactin. We suggested the uptake of Iron(III) by the DHBS complex. DHBS production by S. maltophilia K279a could be attributed to an incomplete enterobactin pathway. Drugs targeting DHBS synthesis could prevent S. maltophilia infection.