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Identifying protein–protein interaction (PPI) site is an important step in understanding biological activity, apprehending pathological mechanism and designing novel drugs. Developing reliable computational methods for predicting PPI site as screening tools contributes to reduce lots of time and expensive costs for conventional experiments, but how to improve the accuracy is still challenging. We propose a PPI site predictor, called Augmented Graph Attention Network Protein-Protein Interacting Site (AGAT-PPIS), based on AGAT with initial residual and identity mapping, in which eight AGAT layers are connected to mine node embedding representation deeply. AGAT is our augmented version of graph attention network, with added edge features. Besides, extra node features and edge features are introduced to provide more structural information and increase the translation and rotation invariance of the model. On the benchmark test set, AGAT-PPIS significantly surpasses the state-of-the-art method by 8% in Accuracy, 17.1% in Precision, 11.8% in F1-score, 15.1% in Matthews Correlation Coefficient (MCC), 8.1% in Area Under the Receiver Operating Characteristic curve (AUROC), 14.5% in Area Under the Precision-Recall curve (AUPRC), respectively.

Superconducting materials have extremely high application value in our life. At present, the discovery of new superconducting materials relies on the experience of experts through a large number of "trial and error" experiments. Obtaining the properties of superconductors also requires a large number of experiments. In this paper, we propose to use the XGBoost model to identify superconductors, reaching 0.986 in accuracy. We apply the deep forest algorithm to predict the critical temperature of superconductors and the coefficient of determination reaches 0.944. We propose to apply the same algorithm to predict the forbidden band width of materials and the coefficient of determination reaches 0.917. A new sub-network structure is constructed to predict the Fermi level of materials and the coefficient of determination reaches 0.984. All of these algorithms have state-of-the-art performance. Finally, the model is tested with a publicly available dataset to identify 50 candidate superconducting materials with a critical temperature greater than 90K.

Laryngeal squamous cell carcinoma (LSCC) is the most common malignant head and neck cancer, with a 40% recurrence rate in the first 3 years after radical treatment. Recurrence of LSCC mostly comprises lymphogenous metastasis, hematogenic metastasis, and locoregional recurrence, while LSCC seeding is rarest: there are only 4 cases reported in PubMed, and none of them is one of subcutaneous seeding. We report a case with post-surgery subcutaneous seeding of LSCC. The final biopsy demonstrated that the subcutaneous seeding of the LSCC was 2 cm away from the primary lesion, with no recurrent foci observed in the larynx and tracheostoma and little relation to the primary lesion. Thus, we drew the conclusion that LSCC surgeries should stick to the principle of the non-tumor technique to prevent subcutaneous seeding.

Background and aim: Small ubiquitin–like modifier (SUMO)-specific protease (SENP)3 is a protease molecule that responds to reactive oxygen species (ROS) with high sensitivity. However, the role of ROS and SENP3 in the formation of nasal polyps (NPs) remains unclear. This study aimed to explore how SENP3 influenced the outcome of chronic rhinosinusitis (CRS) by altering macrophage function, that is, the formation of NPs. Methods: The alternative activation of macrophage (M2) was detected with CD68+CD206+ in humans and CD206+ in mice. The nasal mucosa of patients with CRS was tested using flow cytometry (CD68, CD80, and CD206) and triple-color immunofluorescence staining (CD68, CD206, and SENP3). The bone marrow–derived macrophages from SENP3 knockout and control mice were stimulated with interleukin (IL)-4 and IL-13 to analyze alternative macrophage polarization in vitro. An animal model of eosinophil infiltration rhinitis was constructed using SENP3 knockout mice. CD206 was detected by immunofluorescence staining. The thickening of eosinophil-infiltrated mucosa was detected by Luna staining. Results: The number of CD68+ CD206+ M2 increased in the nasal mucosa of patients with CRS with NP (CRSwNP) compared with patients with CRS without NP (CRSsNP), but with no significant difference between the groups. SENP3 knockout increased the polarization of F4/80+CD206+M2. Meanwhile, the number of CD206+M2 significantly increased in the osinophil infiltration rhinitis model constructed using SENP3 knockout mice and controls, with a more obvious proliferation of the nasal mucosa. Conclusion: The downregulation of the expression of macrophage SENP3 in the nasal mucosa in osinophil infiltration rhinitis promoted the formation of NPs. Trial registration: This study was retrospective and did not involve any health interventions for human participants.

Monitoring the operating status of a High-Speed Train (HST) at any moment is necessary to ensure its security. Multi-channel vibration signals are collected by sensors installed on bogies and beneficial information are extracted to determine the running condition. Based on multi-view clustering and considering different views of complementary information, this study proposes a Multi-view Kernel Fuzzy C-Means (MvKFCM) model for condition recognition of the HST bogie. First, fast Fourier transform coefficients of HST vibration signals of all channels are extracted. Then, the fuzzy classification coefficient of every channel is calculated after clustering to select the appropriate channels. Finally, the selected channels are used to cluster by MvKFCM and the conditions of HST are determined. Experimental results show that the selection is effective to maintain rich feature information and remove redundancy. Furthermore, the condition recognition rate of MvKFCM is higher than that of single-view and four other multiple-view clustering algorithms.

Based on the multi-source and heterogeneous characteristics of massive state sensing data of bridges, this paper establishes a multi-source heterogeneous bridge state sensing data feature extraction and analysis method. A dynamic evaluation model of bridge technology based on multi-source heterogeneous data fusion is proposed. For the first time, the relationship between multi-source perceptual data and bridge infrastructure technology is established, the knowledge graph of bridge infrastructure technology is constructed, and the relationship between various state-aware data and bridge technology is explicitly expressed by the map. This collaborative association is used to dynamically evaluate and predict bridge technology.

The aim of this study was to assess morphological features of intact adipose tissue (AT) ex vivo from both subcutaneous (s.c.) abdominal and gluteal areas using a novel approach of multiphoton autofluorescence microscopy (MPAM) combined with second harmonic generation microscopy (SHGM), and to assess the relationship between morphological features in the two AT sites and insulin resistance to peripheral glucose disposal.This study was a cross-sectional evaluation of AT morphology feature and peripheral insulin resistance.Fourteen overweight/obese premenopausal women underwent body composition studies, hyperinsulinemic-euglycemic clamps, and needle biopsy of both the s.c. abdominal and gluteal AT areas. MPAM combined with SHGM was used to measure adipocyte maximal diameter and collagen fiber bundle thickness within a sampled image volume after three-dimensional visualization.Higher body mass index (BMI) was associated with larger adipocyte diameter in s.c. abdominal, but not gluteal, AT. Higher adipocyte diameter was associated with higher pericellular collagen thickness. Adipocyte diameter in s.c. abdominal, but not gluteal, AT was associated positively with leptin and negatively with adiponectin plasma levels and peripheral glucose disposal rate. The latter correlation was no longer significant after adjustment for collagen thickness.In overweight/obese premenopausal women, larger adipocyte diameter in s.c. abdominal, but not gluteal, AT associates with low plasma adiponectin and systemic insulin resistance, and suggests that increased collagen thickness (obesity-related scarring) could contribute to these findings.

Precoding methods at the Base Station (BS) can be used to deal with the inter-cell interference and improve the signal quality of the user especially at the cell edge. In this paper, a novel Zero-Forcing (ZF) precoding method is proposed and investigated for multi-cell Multi-Input Multi-Output (MIMO) systems. We propose a relaxed ZF precoding method by relaxing the ZF criterion to some degree so that the inter-cell interference may not be zero. Complexity analysis shows that compared with the conventional ZF method, the additional computation complexity for the proposed method is trivial. Simulation results show that the proposed relaxed ZF method has better performance than the conventional ZF method in terms of the sum-rate, especially at low Signal to Noise Ratio (SNR).

We develop an efficient hard detector for multiple-input multiple-output (MIMO) channels, which adaptively combines maximum-likelihood detection (MLD) and minimum-mean-square error with a successive interference canceler together. Unlike the conventional joint combination scheme, which may suffer from considerable degradation in bit-error-rate (BER) performance over correlated channels and where only one data stream is detected by MLD, our proposed scheme adaptively controls the number of data streams to be detected by MLD based on an analytical characterization of reliability for the detection. Simulation results illustrate that near-optimal BER performance can be obtained at much lower computational complexity by the proposed method as compared with existing techniques, regardless of the spatial correlation of the MIMO channels. Copyright © 2012 John Wiley & Sons, Ltd.

Ehrlichia are obligately intracellular bacteria that reside in a vacuole in the cytoplasm of phagocytes. We determined by confocal microscopy the interaction between Ehrlichia and mitochondria in DH82 cells to investigate the mechanism of Ehrlichia survival inside the phagocyte. The most remarkable finding of our study was that Ehrlichia morulae interacted with mitochondria and inhibited mitochondrial metabolism. We showed that in Ehrlichia chaffeensis-infected DH82 cells, mitochondria did not incorporate BrdU and transcriptional level of the mitochondrial gene NADPH2 was significantly reduced, indicating the inhibition of mitochondrial metabolism. This study demonstrates that Ehrlichia are able to inhibit mitochondrial activities, and it opens up a new avenue for the study of Ehrlichia pathogenesis.

This paper discusses the document clustering and visualization process: analyzing documents index, clustering document, and visualizing exploration. It focuses on ant-based clustering algorithm and some significant improvements. Clusterings are formed on the plane by ants walking, picking up or dropping down projected document vectors with different probability. It is shown that the similar documents appear in spatial proximity, whereas unrelated documents are clearly separated in visual space.