In our recent work on denoising, a linear combination of five features was used to adjust the peak intensities in tandem mass spectra. Although the method showed a promise, the coefficients (weights) ...of the linear combination were fixed and determined empirically. In this paper, we proposed an adaptive approach for estimating these weights. The proposed approach: (i) calculates the score for each peak in a data set with the previous empirically determined weights, (ii) selects the training data set based on the scores of peaks, (iii) applies the linear discriminant analysis to the training data set and takes the solution of linear discriminant analysis as the new weights, (iv) calculates the score again with the new weights, (v) repeats (ii)–(iv) until the weights have no significant change. After getting the final weights, the proposed approach follows the previous methods. The proposed approach was applied to two tandem mass spectra data sets: ISB (with low resolution) and TOV‐Q (with high resolution) to evaluate its performance. The results show that about 66% of peaks (likely noise peaks) can be removed and that the number of peptides identified by MASCOT increases by 14 and 23.4% for ISB and TOV‐Q data set, respectively, compared to the previous work.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
In literature, hundreds of features have been proposed to assess the quality of tandem mass spectra. However, many of these features are irrelevant in describing the spectrum quality and they can ...degenerate the spectrum quality assessment performance. We propose a two-stage Recursive Feature Elimination based on Support Vector Machine (SVM-RFE) method to select the highly relevant features from those collected in literature. Classifiers are trained to verify the relevance of selected features. The results demonstrate that these selected features can better describe the quality of tandem mass spectra and hence improve the performance of tandem mass spectrum quality assessment.
Next generation sequencing has now enabled a cost-effective enumeration of the full mutational complement of a tumor genome-in particular single nucleotide variants (SNVs). Most current computational ...and statistical models for analyzing next generation sequencing data, however, do not account for cancer-specific biological properties, including somatic segmental copy number alterations (CNAs)-which require special treatment of the data. Here we present CoNAn-SNV (Copy Number Annotated SNV): a novel algorithm for the inference of single nucleotide variants (SNVs) that overlap copy number alterations. The method is based on modelling the notion that genomic regions of segmental duplication and amplification induce an extended genotype space where a subset of genotypes will exhibit heavily skewed allelic distributions in SNVs (and therefore render them undetectable by methods that assume diploidy). We introduce the concept of modelling allelic counts from sequencing data using a panel of Binomial mixture models where the number of mixtures for a given locus in the genome is informed by a discrete copy number state given as input. We applied CoNAn-SNV to a previously published whole genome shotgun data set obtained from a lobular breast cancer and show that it is able to discover 21 experimentally revalidated somatic non-synonymous mutations in a lobular breast cancer genome that were not detected using copy number insensitive SNV detection algorithms. Importantly, ROC analysis shows that the increased sensitivity of CoNAn-SNV does not result in disproportionate loss of specificity. This was also supported by analysis of a recently published lymphoma genome with a relatively quiescent karyotype, where CoNAn-SNV showed similar results to other callers except in regions of copy number gain where increased sensitivity was conferred. Our results indicate that in genomically unstable tumors, copy number annotation for SNV detection will be critical to fully characterize the mutational landscape of cancer genomes.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
AbstractThe development and application of asphalt plug joints have gained popularity due to their unique advantages, such as driving comfort, shock absorption, noise reduction, and convenient ...management and maintenance. However, these expansion joints are susceptible to damage at the interface due to long-term exposure to traffic loads and environmental factors. Specifically, the interface bond damage between the asphalt plug joint and the pavement directly impacts the service performance and durability of bridge expansion joints. To address these issues effectively, this paper proposes an interface binder with improved bonding performance based on pull-off and oblique shear tests, which is used to enhance the interface cracking resistance of the asphalt plug joint structure. The research focused on the interface layer between Marshall and concrete specimens. A finite-element model of the pull-off specimen, which includes a bilinear cohesive element, was established to simulate the cohesive damage process between the interface layers. The constitutive relationship of the bilinear cohesive element utilizes the bond-slip constitutive curve obtained from the tests. It combines the maximum nominal stress (Maxs criterion) and the linear softening method of energy to simulate the fracture process of the interface layer. The simulation results were compared with the experimental data. Additionally, a parameter design analysis was conducted to study the influence of individual parameter variables on the interface damage behavior. The analysis provided robust data support for simulating the interfacial crack resistance. The results indicate that the simulation analysis aligned well with the experimental data, and the bilinear cohesive model can effectively capture the nonlinear behavior of the interface layer bond-slip. The loading method and the type of binder were found to have a significant impact on the interface bond fracture energy. The results demonstrate the effectiveness of the proposed approach in capturing the nonlinear behavior of the interface layer and provide valuable insights into the influence of different parameters on interface damage behavior.
To accommodate the changing needs of the developing brain, microglia must undergo substantial morphological, phenotypic, and functional reprogramming. Here, we examined whether cellular metabolism ...regulates microglial function during neurodevelopment. Microglial mitochondria bioenergetics correlated with and were functionally coupled to phagocytic activity in the developing brain. Transcriptional profiling of microglia with diverse metabolic profiles revealed an activation signature wherein the interleukin (IL)-33 signaling axis is associated with phagocytic activity. Genetic perturbation of IL-33 or its receptor ST2 led to microglial dystrophy, impaired synaptic function, and behavioral abnormalities. Conditional deletion of Il33 from astrocytes or Il1rl1, encoding ST2, in microglia increased susceptibility to seizures. Mechanistically, IL-33 promoted mitochondrial activity and phagocytosis in an AKT-dependent manner. Mitochondrial metabolism and AKT activity were temporally regulated in vivo. Thus, a microglia-astrocyte circuit mediated by the IL-33-ST2-AKT signaling axis supports microglial metabolic adaptation and phagocytic function during early development, with implications for neurodevelopmental and neuropsychiatric disorders.
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•Phagocytic activity and bioenergetics are coupled in microglia during development•Astrocyte-derived IL-33 promotes microglial engulfment and bioenergetics via AKT•Loss of ST2 and IL-33 results in microglial dysfunction and susceptibility to seizures•Microglial mitochondrial metabolism and AKT activity are temporally regulated in vivo
Microglia are capable of diverse functions to accommodate the changing needs of the central nervous system during development. He et al. define a microglia-astrocyte circuit mediated by the IL-33-ST2-AKT signaling axis that supports microglial metabolic adaptation and phagocytic function during early development, with implications for neurodevelopmental and neuropsychiatric disorders.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Signaling abnormalities in immune responses in the small intestine can trigger chronic type 2 inflammation involving interaction of multiple immune cell types. To systematically characterize this ...response, we analyzed 58,067 immune cells from the mouse small intestine by single-cell RNA sequencing (scRNA-seq) at steady state and after induction of a type 2 inflammatory reaction to ovalbumin (OVA). Computational analysis revealed broad shifts in both cell-type composition and cell programs in response to the inflammation, especially in group 2 innate lymphoid cells (ILC2s). Inflammation induced the expression of exon 5 of Calca, which encodes the alpha-calcitonin gene-related peptide (α-CGRP), in intestinal KLRG1+ ILC2s. α-CGRP antagonized KLRG1+ ILC2s proliferation but promoted IL-5 expression. Genetic perturbation of α-CGRP increased the proportion of intestinal KLRG1+ ILC2s. Our work highlights a model where α-CGRP-mediated neuronal signaling is critical for suppressing ILC2 expansion and maintaining homeostasis of the type 2 immune machinery.
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•scRNA-seq reveals intestinal immune cell programs in allergic inflammation•Intestinal KLRG1+ ILC2s express α-CGRP and its receptors•α-CGRP regulates type 2 cytokine production of KLRG1+ ILC2s•α-CGRP maintains KLRG1+ ILC2 homeostasis and the type 2 immune machinery
Allergic inflammation involves the interaction of multiple immune cell types, as well as their crosstalk with other physiological systems, such as neurons. By establishing intestinal immune cell atlas at different states, Xu et al. identify that neuropeptide α-CGRP modulates group 2 innate lymphoid cell responses and the allergic reaction.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The evolution of cancer genomes within a single tumor creates mixed cell populations with divergent somatic mutational landscapes. Inference of tumor subpopulations has been disproportionately ...focused on the assessment of somatic point mutations, whereas computational methods targeting evolutionary dynamics of copy number alterations (CNA) and loss of heterozygosity (LOH) in whole-genome sequencing data remain underdeveloped. We present a novel probabilistic model, TITAN, to infer CNA and LOH events while accounting for mixtures of cell populations, thereby estimating the proportion of cells harboring each event. We evaluate TITAN on idealized mixtures, simulating clonal populations from whole-genome sequences taken from genomically heterogeneous ovarian tumor sites collected from the same patient. In addition, we show in 23 whole genomes of breast tumors that the inference of CNA and LOH using TITAN critically informs population structure and the nature of the evolving cancer genome. Finally, we experimentally validated subclonal predictions using fluorescence in situ hybridization (FISH) and single-cell sequencing from an ovarian cancer patient sample, thereby recapitulating the key modeling assumptions of TITAN.
Mass spectrometers can produce a large number of tandem mass spectra. They are unfortunately noise-contaminated. Noises can affect the quality of tandem mass spectra and thus increase the false ...positives and false negatives in the peptide identification. Therefore, it is appealing to develop an approach to denoising tandem mass spectra.
We propose a novel approach to denoising tandem mass spectra. The proposed approach consists of two modules: spectral peak intensity adjustment and intensity local maximum extraction. In the spectral peak intensity adjustment module, we introduce five features to describe the quality of each peak. Based on these features, a score is calculated for each peak and is used to adjust its intensity. As a result, the intensity will be adjusted to a local maximum if a peak is a signal peak, and it will be decreased if the peak is a noisy one. The second module uses a morphological reconstruction filter to remove the peaks whose intensities are not the local maxima of the spectrum. Experiments have been conducted on two ion trap tandem mass spectral datasets: ISB and TOV. Experimental results show that our algorithm can remove about 69% of the peaks of a spectrum. At the same time, the number of spectra that can be identified by Mascot algorithm increases by 31.23% and 14.12% for the two tandem mass spectra datasets, respectively.
The proposed denoising algorithm can be integrated into current popular peptide identification algorithms such as Mascot to improve the reliability of assigning peptides to spectra. AVAILABILITY OF THE SOFTWARE: The software created from this work is available upon request.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Neutrophils are implicated in multiple homeostatic and pathological processes, but whether functional diversity requires discrete neutrophil subsets is not known. Here, we apply single-cell RNA ...sequencing to neutrophils from normal and inflamed mouse tissues. Whereas conventional clustering yields multiple alternative organizational structures, diffusion mapping plus RNA velocity discloses a single developmental spectrum, ordered chronologically. Termed here neutrotime, this spectrum extends from immature pre-neutrophils, largely in bone marrow, to mature neutrophils predominantly in blood and spleen. The sharpest increments in neutrotime occur during the transitions from pre-neutrophils to immature neutrophils and from mature marrow neutrophils to those in blood. Human neutrophils exhibit a similar transcriptomic pattern. Neutrophils migrating into inflamed mouse lung, peritoneum and joint maintain the core mature neutrotime signature together with new transcriptional activity that varies with site and stimulus. Together, these data identify a single developmental spectrum as the dominant organizational theme of neutrophil heterogeneity.
Hodgkin lymphoma is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of noncancerous immune cells with rare malignant cells. Characterization of the ...cellular components and their spatial relationship is crucial to understanding cross-talk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 Hodgkin lymphoma tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the Hodgkin lymphoma-specific immune microenvironment at single-cell resolution. Single-cell expression profiling identified a novel Hodgkin lymphoma-associated subset of T cells with prominent expression of the inhibitory receptor LAG3, and functional analyses established this LAG3
T-cell population as a mediator of immunosuppression. Multiplexed spatial assessment of immune cells in the microenvironment also revealed increased LAG3
T cells in the direct vicinity of MHC class II-deficient tumor cells. Our findings provide novel insights into TME biology and suggest new approaches to immune-checkpoint targeting in Hodgkin lymphoma. SIGNIFICANCE: We provide detailed functional and spatial characteristics of immune cells in classic Hodgkin lymphoma at single-cell resolution. Specifically, we identified a regulatory T-cell-like immunosuppressive subset of LAG3
T cells contributing to the immune-escape phenotype. Our insights aid in the development of novel biomarkers and combination treatment strategies targeting immune checkpoints.
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