Prior knowledge-guided multilevel graph neural network for tumor risk prediction and interpretation via multi-omics data integration.

The interrelation and complementary nature of multi-omics data can provide valuable insights into the intricate molecular mechanisms underlying diseases. However, challenges such as limited sample size, high data dimensionality and differences in omics modalities pose significant obstacles to fully harnessing the potential of these data. The prior knowledge such as gene regulatory network and pathway information harbors useful gene-gene interaction and gene functional module information. To effectively integrate multi-omics data and make full use of the prior knowledge, here, we propose a Multilevel-graph neural network (GNN): a hierarchically designed deep learning algorithm that sequentially leverages multi-omics data, gene regulatory networks and pathway information to extract features and enhance accuracy in predicting survival risk. Our method achieved better accuracy compared with existing methods. Furthermore, key factors nonlinearly associated with the tumor pathogenesis are prioritized by employing two interpretation algorithms (i.e. GNN-Explainer and IGscore) for neural networks, at gene and pathway level, respectively. The top genes and pathways exhibit strong associations with disease in survival analyses, many of which such as SEC61G and CYP27B1 are previously reported in the literature.

Nonreciprocal topological mode conversion by encircling an exceptional point in dynamic waveguides.

The topology of exceptional points (EPs) has been revealed by taking stationary or dynamical encircling around them, which induces eigenstate exchange or chiral mode conversion. However, the conversions are usually reciprocal obeying restricted transmittances. Here we propose the concept of nonreciprocal encircling of EPs in a dynamic waveguide under complex modulation. The waveguide allows direction-dependent EPs in their quasienergy spectra due to different phase-matching conditions for opposite propagation direction. We design a closed loop that will encircle the EP in the backward direction but not in the forward direction. In this way, a nonreciprocal topological conversion is achieved as the forward transmittance from the even to odd mode significantly exceeds the backward transmittance from the odd to even mode. As a result, the forward propagation produces two modes with equal strength while the backward propagation leads to a specific mode regardless of the input. The structure is promising for making robust optical isolators.

Solution Evolution Knowledge Service Based on Design Iteration in Strain Sensor Design.

Product design is a process of repeated iteration and gradual improvement, and knowledge push is one of the bottlenecks that needs to be solved to improve the product design level. With the increase in design complexity and iteration rounds, the existing knowledge application methods can hardly meet the needs of product design solution iteration and evolution. In order to better assist designers in acquiring and applying knowledge in the process of product design solution evolution, a knowledge service method for product design solution evolution based on the problem-strategy-solution (PSS) interaction iteration is proposed. The mapping and feedback process between design problems, design strategies, and design solutions are analyzed, a model of the solution evolution process based on design iteration is proposed, and a PSS-based product design solution evolution mechanism is established. On this basis, the product design solution evolution knowledge service dimension is built, and the solution evolution knowledge service model based on design iteration is established. The corresponding solution evolution function module is developed based on the pre-developed computer-aided product innovation design platform. The validity of the iterated-based design was proved in the technical innovation of nanofiber preparation and further application of strain sensors.

Screening of radiation gastrointestinal injury biomarkers in rat plasma by high-coverage targeted lipidomics.

INTRODUCTION: In the event of radiological accidents and cancer radiotherapies in the clinic, the gastrointestinal (GI) system is vulnerable to ionizing radiation and shows GI injury. Accessible biomarkers may provide means to predict, evaluate, and treat GI tissue damage. The current study investigated radiation GI injury biomarkers in rat plasma. MATERIAL AND METHODS: High-coverage targeted lipidomics was employed to profile lipidome perturbations at 72 h after 0, 1, 2, 3, 5, and 8 Gy (60Co γ-rays at 1 Gy/min) total-body irradiation in male rat jejunum. The results were correlated with previous plasma screening outcomes. RESULTS: In total, 93 differential metabolites and 28 linear dose-responsive metabolites were screened in the jejunum. Moreover, 52 lipid species with significant differences both in jejunum and plasma were obtained. Three lipid species with linear dose-response relationship both in jejunum and plasma were put forth, which exhibited good to excellent sensitivity and specificity in triaging different exposure levels. DISCUSSION: The linear dose-effect relationship of lipid metabolites in the jejunum and the triage performance of radiation GI injury biomarkers in plasma were studied for the first time. CONCLUSION: The present study can provide insights into expanded biomarkers of IR-mediated GI injury and minimally invasive assays for evaluation.

Screening of Lipids for Early Triage and Dose Estimation after Acute Radiation Exposure in Rat Plasma Based on Targeted Lipidomics Analysis.

Rapid early triage and dose estimation is vital for limited medical resource allocation and treatment of a large number of the wounded after radiological accidents. Lipidomics has been utilized to delineate biofluid lipid signatures after irradiation. Here, high-coverage targeted lipidomics was employed to screen radiosensitive lipids after 0, 1, 2, 3, 5, and 8 Gy total body irradiation at 4, 24, and 72 h postirradiation in rat plasma. Ultra-performance liquid chromatography-tandem mass spectrometry with a multiple reaction monitoring method was utilized. In total, 416 individual lipids from 18 major classes were quantified and those biomarkers altered in a dose-dependent manner constituted panel A-panel D. Receiver operator characteristic curve analysis using combined lipids showed good to excellent sensitivity and specificity in triaging different radiation exposure levels (area under curve = 0.814-1.000). The equations for dose estimation were established by stepwise regression analysis for three time points. A novel strategy for radiation early triage and dose estimation was first established and validated using panels of lipids. Our study suggests that it is feasible to acquire quantitative lipid biomarker panels using targeted lipidomics platforms for rapid, high-throughput triage, which can provide further insights in developing lipidomics strategies for radiation biodosimetry in humans.

Efficient Mode Transfer on a Compact Silicon Chip by Encircling Moving Exceptional Points.

Exceptional points (EPs) are branch point singularities of self-intersecting Riemann sheets, and they can be observed in a non-Hermitian system with complex eigenvalues. It has been revealed recently that dynamically encircling EPs by adiabatically changing the parameters of a system composed of lossy optical waveguides could lead to asymmetric (input-output) mode transfer. However, the length of the waveguides had to be considerable to ensure adiabatic evolution. Here we demonstrate that the parameters can change adiabatically along a smaller encircling loop by utilizing moving EPs, leading to significant shortening of the structures compared to fixed EPs. Meanwhile, the mode transmittance is remarkably improved and the transfer efficiency persists at ∼90%. Moving EPs are very promising for applications such as highly integrated broadband optical switches and convertors operating at telecommunication wavelengths.

In-situ electromechanical testing and loading system for dynamic cell-biomaterial interaction study.

The mechanical and electrical properties of biomaterials are essential in cell function regulation during cell-biomaterial interaction. However, previous studies focused on probing cell regulation mechanisms under one type of stimulus, and a platform that enables the study of electromechanical coupling effects of a biomaterial on cells is still lacking. Here, we present an in-situ electromechanical testing and loading system to image live cells when co-cultured with electroactive biomaterials. The system can provide accurate and repeatable stretch on biomaterials and cells to mimic in vivo tension microenvironment. Besides, the integrated displacement transducer, force sensor, and electrical signal detector enable the real time detection of electromechanical signals on electroactive biomaterials under various stretch loading. Combined with a microscope, live cell imaging can be realized to probe cell behavior. The feasibility of the system is validated by culturing mesenchymal stem cells on piezoelectric nanofiber and conductive hydrogel. Experiment results show the device as a reliable and accurate tool to investigate electromechanical properties of biomaterials and probe essential features of live cells. Our system provides a way to correlate cell behavior with electromechanical cues directly and is useful for exploration of cell function during cell-biomaterial interaction.

Online Multiple Athlete Tracking with Pose-Based Long-Term Temporal Dependencies.

This paper addresses the Multi-Athlete Tracking (MAT) problem, which plays a crucial role in sports video analysis. There exist specific challenges in MAT, e.g., athletes share a high similarity in appearance and frequently occlude with each other, making existing approaches not applicable for this task. To address this problem, we propose a novel online multiple athlete tracking approach which make use of long-term temporal pose dynamics for better distinguishing different athletes. Firstly, we design a Pose-based Triple Stream Network (PTSN) based on Long Short-Term Memory (LSTM) networks, capable of modeling long-term temporal pose dynamics of athletes, including pose-based appearance, motion and athletes' interaction clues. Secondly, we propose a multi-state online matching algorithm based on bipartite graph matching and similarity scores produced by PTSN. It is robust to noisy detections and occlusions due to the reliable transitions of multiple detection states. We evaluate our method on the APIDIS, NCAA Basketball and VolleyTrack databases, and the experiment results demonstrate its effectiveness.

Multi-Scale Global Contrast CNN for Salient Object Detection.

Salient object detection (SOD) is a fundamental task in computer vision, which attempts to mimic human visual systems that rapidly respond to visual stimuli and locate visually salient objects in various scenes. Perceptual studies have revealed that visual contrast is the most important factor in bottom-up visual attention process. Many of the proposed models predict saliency maps based on the computation of visual contrast between salient regions and backgrounds. In this paper, we design an end-to-end multi-scale global contrast convolutional neural network (CNN) that explicitly learns hierarchical contrast information among global and local features of an image to infer its salient object regions. In contrast to many previous CNN based saliency methods that apply super-pixel segmentation to obtain homogeneous regions and then extract their CNN features before producing saliency maps region-wise, our network is pre-processing free without any additional stages, yet it predicts accurate pixel-wise saliency maps. Extensive experiments demonstrate that the proposed network generates high quality saliency maps that are comparable or even superior to those of state-of-the-art salient object detection architectures.

Topological bound modes in anti-PT-symmetric optical waveguide arrays.

We investigate the topological bound modes in a binary optical waveguide array with anti-parity-time (PT) symmetry. The anti-PT-symmetric arrays are realized by incorporating additional waveguides to the bare arrays, such that the effective coupling coefficients are imaginary. The systems experience two kinds of phase transition, including global topological order transition and quantum phase transition. As a result, the system supports two kinds of robust bound modes, which are protected by the global topological order and the quantum phase, respectively. The study provides a promising approach to realizing robust light transport by utilizing mediating components.

Uniform field electrospinning for 3D printing of fibrous configurations as strain sensors.

Electrospinning is becoming an efficient method to produce fibers in the submicron range, but the bending instability of conventional electrospinning system (CES) brings limitations in the distinctive deposition of electrospun fibers. Herein, we proposed a strategy to update the electrospinning system through establishment of a uniform electric field, realizing 3D printing of electrospun fibers with well-controlled, low-cost, and template-free manners. The uniform field electrospinning (UFES) apparatus is configured by inserting the electrospinning nozzle into the center of an aided metal plate. The electric field simulation of UFES indicates a uniform distribution between the aided metal plate and the collector, while a diverging and weaker electric field is produced by CES. The collector of UFES is mounted on a translation stage, which moves along x and y axes under computer control. The distinctive deposition of electrospun fibers produces fibrous mats with rectangular patterns of different grid sizes, and butterfly and TaiJi figures with high resolutions are directly written by UFES. The layer-by-layer deposition of electrospun fibers under UFES produces microscale Mongolian yurts with distinct hollow structure. Fibrous blocks with an average width of 120 µm and height of 630 µm were printed by UFES from conductive polymer composites and constructed into strain sensors. The electric current strength of fibrous microblocks changes sharply in response to the finger bending and release, indicating the capability to monitor human motions. Thus, this study demonstrates that the UFES becomes an easy-handling strategy for 3D printing of electrospun fibers to create complex geometries.

Meta-analysis of Nicorandil effectiveness on myocardial protection after percutaneous coronary intervention.

BACKGROUND: Using the current meta-analysis as well as systematic review, to determine the curative effect of Nicorandil in comparison of no Nicorandil after elective percutaneous coronary intervention(PCI) on patients. METHODS: Published literatures were identified via a computerized literature search of CENTRAL, PubMed, Cochrane, Embase Databases of Systematic Reviews. A set of randomized trials evaluating Nicorandil in comparison of no Nicorandil administered following PCI in patients harboring coronary artery disease were included. Outcomes were revealed based on the following parameters: peak creatine kinase-MB (CK-MB) value, left ventricular ejection fraction (LVEF), peak troponin I (cTnI), and major adverse cardiovascular events (MACEs) per randomized patients. RESULTS: We included a total of 14 RCTs involving 1864 subjects in the present review. According to this meta-analysis, LVEF was significantly improved in Nicorandil group; the peak CK-MB level and the incidence of adverse cardiovascular events were remarkably lower in Nicorandil group. Nicorandil and no Nicorandil administered group appeared to be equivalent with regards to cTnI. CONCLUSIONS: Nicorandil is effective for patients undergoing elective PCI with coronary artery disease in terms of reducing the incidence of adverse cardiovascular events as well as improving heart function. Nicorandil may exert potential role as a valid and adjunctive therapy accompanied with PCI.

Automatic Building Extraction from Google Earth Images under Complex Backgrounds Based on Deep Instance Segmentation Network.

Building damage accounts for a high percentage of post-natural disaster assessment. Extracting buildings from optical remote sensing images is of great significance for natural disaster reduction and assessment. Traditional methods mainly are semi-automatic methods which require human-computer interaction or rely on purely human interpretation. In this paper, inspired by the recently developed deep learning techniques, we propose an improved Mask Region Convolutional Neural Network (Mask R-CNN) method that can detect the rotated bounding boxes of buildings and segment them from very complex backgrounds, simultaneously. The proposed method has two major improvements, making it very suitable to perform building extraction task. Firstly, instead of predicting horizontal rectangle bounding boxes of objects like many other detectors do, we intend to obtain the minimum enclosing rectangles of buildings by adding a new term: the principal directions of the rectangles θ. Secondly, a new layer by integrating advantages of both atrous convolution and inception block is designed and inserted into the segmentation branch of the Mask R-CNN to make the branch to learn more representative features. We test the proposed method on a newly collected large Google Earth remote sensing dataset with diverse buildings and very complex backgrounds. Experiments demonstrate that it can obtain promising results.

Photonic Weyl phase transition in dynamically modulated brick-wall waveguide arrays.

We investigate the topological phase transition between Type-I and Type-II Weyl points (WPs) in a composite three-dimensional lattice composed of a two-dimensional brick-wall waveguide array and a synthetic frequency dimension created by dynamic modulation. By imposing different modulation amplitudes and phases in the two sublattices, we can break either parity or time-reversal symmetry and realize the phase transition between Type-I and Type-II WPs. As the array is truncated to have two edges, two Fermi-arc surface states will emerge, which propagate in opposite directions for Type-I WPs while in same directions for Type-II WPs, accompanied by bidirectional and unidirectional frequency shifts for the optical modes. Particularly at the phase transition point, we find that one of two bands becomes flat with a vanished group velocity along frequency axis in the vicinity of WPs. The study paves a way towards realizing different topological phases in the same photonic structure, which offers new opportunities to control wave transportation both in spatial and frequency domains.

Giant Goos-Hänchen shifts in non-Hermitian dielectric multilayers incorporated with graphene.

We theoretically investigate the Goos-Hänchen (GH) shifts of optical beam in a defective photonic crystal composed of dielectric multilayers and graphene. The system is non-Hermitian and possesses exceptional points (EPs) as the scattering matrix becomes defective at the zero points of reflection. The reflective wave at EPs experiences an abrupt phase change and there the eigenvalues of scattering matrix coalesce. The GH shifts are extremely large near EPs in parametric space composed of dielectric refractive index and incident angle. The positive and negative maxima of GH shifts could be as high as 103 times of the incident wavelength. The direction of GH shifts switches at EPs and the EPs position can be readily controlled by the chemical potential of graphene. Moreover, the GH shifts should remarkably change as the incident waves impinge on the structure from opposite directions. The study of GH shifts in the graphene incorporated multilayers may find great applications in highly sensitive sensors.

Conversion of carbazole carboxamide based reversible inhibitors of Bruton's tyrosine kinase (BTK) into potent, selective irreversible inhibitors in the carbazole, tetrahydrocarbazole, and a new 2,3-dimethylindole series.

Incorporation of a suitably-placed electrophilic group transformed a series of reversible BTK inhibitors based on carbazole-1-carboxamide and tetrahydrocarbazole-1-carboxamide into potent, irreversible inhibitors. Removal of one ring from the core of these compounds provided a potent irreversible series of 2,3-dimethylindole-7-carboxamides having excellent potency and improved selectivity, with the additional advantages of reduced lipophilicity and molecular weight.

Alterations in histone acetylation following exposure to 60Co γ-rays and their relationship with chromosome damage in human lymphoblastoid cells.

Chromosome damage is related to DNA damage and erroneous repair. It can cause cell dysfunction and ultimately induce carcinogenesis. Histone acetylation is crucial for regulating chromatin structure and DNA damage repair. Ionizing radiation (IR) can alter histone acetylation. However, variations in histone acetylation in response to IR exposure and the relationship between histone acetylation and IR-induced chromosome damage remains unclear. Hence, this study investigated the variation in the total acetylation levels of H3 and H4 in human lymphocytes exposed to 0-2 Gy 60Co γ-rays. Suberoylanilide hydroxamic acid (SAHA), a histone deacetylase (HDAC) inhibitor, was added to modify the histone acetylation state of irradiated cells. Then, the total acetylation level, enzyme activity, dicentric plus centric rings (dic + r) frequencies, and micronucleus (MN) frequencies of the treated cells were analyzed. Results indicated that the acetylation levels of H3 and H4 significantly decreased at 1 and 24 h, respectively, after radiation exposure. The acetylation levels of H3 and H4 in irradiated groups treated with SAHA were significantly higher than those in irradiated groups that were not treated with SAHA. SAHA treatment inhibited HDAC activity in cells exposed to 0-1 Gy 60Co γ-rays. SAHA treatment significantly decreased dic + r/cell and MN/cell in cells exposed to 0.5 or 1.0 Gy 60Co γ-rays relative to that in cells that did not receive SAHA treatment. In conclusion, histone acetylation is significantly affected by IR and is involved in chromosome damage induced by 60Co γ-radiation.

Exceptional points in Fano-resonant graphene metamaterials.

We investigate the optical exceptional points (EPs) in the graphene incorporated multilayer metamaterial manifesting Fano resonance. The system is non-Hermitian and possesses EPs where both the eigenvalues and eigenvectors of the Hamiltonian coalesce. In the aid of Fano resonance, the reflection may reach minimum approaching to zero, resulting in the degeneration of both eigenvalues and eigenvectors and thus the emergence of EPs. The transmission and reflection of light through the metamaterial change sharply by varying slightly the incident wavelength and chemical potential of graphene in the parameter space when encircling the EPs. In addition, the unidirectional invisibility can be achieved at EPs. The study paves a way to precisely controlling the transmission and reflection through metamaterials and may find applications in optoelectronic switches, modulators, absorbers, and optical sensors.

Genetic basis of Y-linked hearing impairment.

A single Mendelian trait has been mapped to the human Y chromosome: Y-linked hearing impairment. The molecular basis of this disorder is unknown. Here, we report the detailed characterization of the DFNY1 Y chromosome and its comparison with a closely related Y chromosome from an unaffected branch of the family. The DFNY1 chromosome carries a complex rearrangement, including duplication of several noncontiguous segments of the Y chromosome and insertion of ∼160 kb of DNA from chromosome 1, in the pericentric region of Yp. This segment of chromosome 1 is derived entirely from within a known hearing impairment locus, DFNA49. We suggest that a third copy of one or more genes from the shared segment of chromosome 1 might be responsible for the hearing-loss phenotype.

Dose-effect relationships of nucleoplasmic bridges and complex nuclear anomalies in human peripheral lymphocytes exposed to 60Co γ-rays at a relatively low dose.

The dose effect between nucleoplasmic bridges (NPB) and relatively low doses of ionising radiation remains unknown. Accordingly, this study investigated the NPB frequencies in human peripheral blood lymphocytes exposed to low-dose (60)Co γ-rays. Complex anomalies, including fused nuclei (FUS), horse-shoe nuclei (HS) and circular nuclei (CIR), which possibly originated from multiple NPBs, were also scored. Human peripheral blood samples were collected from three healthy males and irradiated with 0-1 and 0-0.4 Gy (60)Co γ-rays. A cytokinesis-block micronucleus cytome assay was then conducted to analyse NPB, PFHC (NPB plus three complex nuclear anomalies) and micronucleus (MN) in binucleated cells. All dose-response curves followed the linear model for both NPB frequency and PFHC cell frequency. The dose-response curves between NPB frequency and absorbed dose at 0-1 and 0-0.4 Gy were y = 0.0037x + 0.0005 (R (2) = 0.979, P < 0.05) and y = 0.0043x + 0.0004 (R (2) = 0.941, P < 0.05), respectively. The dose-response curves between PFHC cell frequency and absorbed dose at 0-1 and 0-0.4 Gy were y = 0.0044x + 0.0007 (R (2) = 0.982, P < 0.05) and y = 0.0059x + 0.0005 (R (2) = 0.969, P < 0.05), respectively. The statistical significance of differences between the irradiated groups (0-0.4 Gy) and background levels of NPB, PFHC and MN were also analysed. The lowest analysable doses of NPB, PFHC and MN were 0.12, 0.08 and 0.08 Gy, respectively. In conclusion, NPBs and PFHC positively correlated with the absorbed radiation at a relatively low dose.