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[Display omitted] The cytokine TSLP promotes type 2 immune responses and can induce adipose loss by stimulating lipid loss from the skin through sebum secretion by sebaceous glands, which enhances the skin barrier. However, the mechanism by which TSLP upregulates sebaceous gland function is unknown. This study investigated the mechanism by which TSLP stimulates sebum secretion and adipose loss. RNA-sequencing analysis was performed on sebaceous glands isolated by laser capture microdissection and single-cell RNA-sequencing analysis was performed on sorted skin T cells. Sebocyte function was analyzed by histological analysis and sebum secretion in vivo and by measuring lipogenesis and proliferation in vitro. This study found that TSLP sequentially stimulated the expression of lipogenesis genes followed by cell death genes in sebaceous glands to induce holocrine secretion of sebum. TSLP did not affect sebaceous gland activity directly. Rather, single-cell RNA-sequencing revealed that TSLP recruited distinct T-cell clusters that produce IL-4 and IL-13, which were necessary for TSLP-induced adipose loss and sebum secretion. Moreover, IL-13 was sufficient to cause sebum secretion and adipose loss in vivo and to induce lipogenesis and proliferation of a human sebocyte cell line in vitro. This study proposes that TSLP stimulates T cells to deliver IL-4 and IL-13 to sebaceous glands, which enhances sebaceous gland function, turnover, and subsequent adipose loss. [ABSTRACT FROM AUTHOR]

This paper first discusses the limitation that the intrinsic mode functions (IMFs) decomposed by the empirical mode decomposition (EMD) in Hilbert-Huang transform (HHT) are not orthogonal. As an improvement to the HHT method, three orthogonal techniques (the forward, backward and arbitrary sequence orthogonalization algorithms) based on the Gram-Schmidt method are then proposed to obtain the completely orthogonal IMFs. According to the orthogonal index and the energy index, the effectiveness of the proposed technique and algorithms is validated through a synthetic signal generated by the combination of three sinusoidal waves with different frequencies and the El Centro (1940, N-S) earthquake accelerogram. By taking the El Centro (1940, N-S) earthquake accelerogram as an example, the problem that whether the orthogonal IMFs satisfy the requirements of IMF is discussed, then the backward and the arbitrary sequence orthogonalization algorithms are recommended. Three historic earthquake accelerograms are analyzed by using the recommended orthogonalization algorithms combined with the Hilbert spectral analysis. The results show that the orthogonal Hilbert spectrum and the orthogonal Hilbert marginal spectrum can produce more faithful representation of earthquake accelerograms than the Hilbert spectrum and the Hilbert marginal spectrum, and they can be used to quantitatively characterize the energy distribution of earthquake accelerograms at different frequency regions. [ABSTRACT FROM AUTHOR]

A numerical study is made on the dynamic through-soil interaction between underground station and nearby pile supported surface structure on viscous-elastic soil layer, under vertically incident S wave. This paper, as a companion of another paper written by the authors [1], focuses on the influence of presence of adjacent surface structure on seismic response of underground structure, while the reference [1] centers on the influence of presence of adjacent underground structure on seismic response of surface structure. To this end, a commercial software product for finite element analysis, ANSYS, has been further developed and enhanced for calculation in frequency domain, in which hysteretic damping can be considered for both the soil and the structures, so that structure-soil-structure interaction (SSSI) can be investigated by via a direct methodology. A discussion is made on the influence of arrangement of structures, distances between structures, shaking direction of seismic wave, shear wave velocity and damping of soil, scale and burial depth of underground structure, storey number, stiffness, style and pile length of surface structure on SSSI, in terms of horizontal relative displacement of underground structure. Maximum relative displacement responses are also presented for 12 seismic inputs. Arrangement and shaking direction are two of the most important factors. The system response can be either amplified or attenuated according to the distance between adjacent structures, related to dynamic properties of the overall system. Those underground structures, surrounded by buildings with the fundamental frequency approximate to that of free field, are heavily affected. [ABSTRACT FROM AUTHOR]

Background N-methyl-N′-nitro-N-nitrosoguanidine (MNNG), an alkylating agent and an environmental carcinogen, causes DNA lesions and even carcinomas. DNA damage responses induced by MNNG activate various DNA repair genes and related signaling pathways. The present study aimed to investigate the regulatory mechanisms of human RR small subunit M2 ( h RRM2) in response to MNNG. Results In this study, we demonstrated that the RRM2 gene was transactivated by MNNG exposure more strongly than the other small subunit, p53R2. The upregulated RRM2 translocated to the nucleus for DNA repair. Further study showed that E2F3 transactivated RRM2 expression by directly binding to its promoter after MNNG exposure. The transactivation was enhanced by the upregulation of NFY, which bound to the RRM2 promoter adjacent to the E2F3 binding site and interacted with E2F3. In response to MNNG treatment, E2F3 accumulated mainly through its phosphorylation at S124 and was dependent on ATR–CHK1 signaling. In comparison, p53R2 played a relatively weaker role in the MNNG-induced DNA damage response, and its transcription was regulated by the ATR–CHK2–E2F1/p53 pathway. Conclusions We suggest that MNNG-stimulated ATR/CHK1 signaling stabilizes E2F3 by S124 phosphorylation, and then E2F3 together with NFY co-transactivate RRM2 expression for DNA repair. General significance We propose a new mechanism for RRM2 regulation to maintain genome stability in response to environmental chemical carcinogens. [ABSTRACT FROM AUTHOR]

Abstract: The dynamic through-soil interaction between underground station and nearby pile supported structure on viscous–elastic soil layer, under vertically incident S wave, is numerically studied. To this end, a commercial software for finite element analysis, ANSYS, has been further developed and enhanced for calculation in frequency domain, in which damping of hysteretic type can be considered for both the soil and the structures, so that structure–soil–structure interaction (SSSI) can be investigated making use of a direct methodology. The influence of arrangement of structures, shaking direction of seismic wave, distances between structures, shear wave velocity, damping of soil, burial depth and number of spans of underground structure on SSSI, in terms of horizontal acceleration magnification factor of ground structure, is addressed. For ground structure, different lengths of pile, stiffnesses, styles, and numbers of storeys and structures are considered. Maximum acceleration responses are also presented for 12 seismic inputs. Arrangement and shaking direction are two of the most important factors. The system response can be either amplified or attenuated according to the distance between adjacent buildings, which has been related to dynamic properties of the overall system. Those neighboring low-slung buildings around underground structure are heavily affected. [Copyright &y& Elsevier]

• An Adaptive Receptive Field Network for mass segmentation in whole mammograms. • The multi-scale attention contributes to the final segmentation results. • The diversity of receptive fields contributes to the segmentation of small masses. UNet adopting an encoder-decoder structure has been used widely in medical image segmentation tasks for its outstanding performance. However, in our work, we find that UNet has the worse segmentation performance of small masses. The reason behind this is that the sizes of receptive fields are limited. In this work, to address this issue, we develop a novel end-to-end model, Adaptive Receptive Field Network (ARF-Net), for the precise breast mass segmentation in whole mammographic images and ultrasound images. ARF-Net composes of an encoder network and a corresponding decoder network, followed by a pixel-wise classifier. In ARF-Net, a Selective Receptive Filed Module (SRFM) is proposed to allocate the suitable sizes of receptive fields to the breast masses of different sizes. SRFM consists of a Multiple Receptive Field Module (MRFM) for generating multiple receptive fields of different sizes and a Multi-Scale Selection Module (MSSM) for selecting the suitable sizes of receptive fields based on the objects' size. The proposed ARF-Net achieves the dice index of 86.1 % , 85.75 % , and 88.12 % on the two mammographic databases (INbreast and CBIS-DDSM) and one ultrasonic database (UDIAT), respectively. Moreover, extensive ablation experiments show that ARF-Net transcends several state-of-the-art segmentation networks, and the developed MSSM exceeds several counterparts. [ABSTRACT FROM AUTHOR]

• An automatic end-to-end convolutional neural network model is designed for breast density classification in mammograms. • By simulating the doctor's reading mechanism, we combine the information of bilateral breasts to classify breast density. • Adaptive spatial attention module (ASAM) and adaptive channel attention module (ACAM), are employed to explore discriminant information for breast density classification. • Proposed BASCNet has been verified on the DDSM and INbreast datasets, and both have achieved state-of-the-art results. Breast density is a significant element for breast cancer precaution. The existing mammographic density classification methods cannot achieve satisfactory classification accuracy while achieving end-to-end. In this paper, we present a novel bilateral adaptive spatial and channel attention network (BASCNet) which integrates the information of the left and right breasts and adaptively pays attention to the discriminative features in spatial and channel dimensions. The proposed BASCNet has been fully proved on the public Digital Database for Screening Mammography (DDSM) and INbreast dataset, and the classification accuracies of 85.10% and 90.51% were achieved with fivefold cross-validation, respectively. Our method is fully automatic and has achieved the classification performance superior to the existing breast density classification methods. Massive ablation experiments were conducted to demonstrate the effectiveness of the network structure. Moreover, we compared the effects of different views (CC and MLO) on breast density classification and verified the effectiveness of the contralateral breast information integration. Overall, the proposed BASCNet has the potential to be applied to clinical diagnosis. [ABSTRACT FROM AUTHOR]

• A Multi-Scale Attention-Guided Network for recognizing abnormalities in mammograms. • The self-adaption and multi-scale contribute to the final classification results. • Multiple receptive fields are beneficial for recognizing objects of different sizes. For the breast mass segmentation in whole mammograms, in our studies, we observe that there is an enormous performance reduction in the case of considering the normal data during training. Therefore, the mammogram classification (normal vs. abnormal) is essential for boosting the breast mass segmentation performance in whole mammograms and is our research topic in this paper. Due to the breast lesions with a variety of sizes, the mammogram classification (normal vs. abnormal) is a challenging task. To improve the mammogram classification performance, we propose an end-to-end convolutional neural network, namely Multi-Scale Attention-Guided Network (MSANet). Specifically, MSANet can be constructed by stacking several Multi-Scale Attention (MSA) bottlenecks. Each MAS bottleneck consists of a Scale Aggregation (SA) unit and a Multi-Scale Attention Module (MSAM). The SA unit is used to generate multiple feature maps of different scales, and the MSAM is used to allocate the suitable size of receptive field for objects of different sizes. According to the extensive experiments, our proposed MSANet-50 achieves a fully automated classification AUC of 0.942 on the DDSM database, which outperforms several approaches. [ABSTRACT FROM AUTHOR]

Chronic hepatitis B virus (HBV) infection is a key factor for hepatocellular carcinoma worldwide. Ribonucleotide reductase (RR) regulates the deoxyribonucleoside triphosphates biosynthesis and serves as a target for anti-cancer therapy. Here, we demonstrate that RR is essential for HBV replication and the viral covalently-closed-circular DNA (cccDNA) synthesis in host liver cells. By performing computer-assisted virtual screening against the crystal structure of RR small subunit M2 (RRM2), osalmid, was identified as a potential RRM2-targeting compound. Osalmid was shown to be 10-fold more active in inhibiting RR activity than hydroxyurea, and significantly inhibited HBV DNA and cccDNA synthesis in HepG2.2.15 cells. In contrast, hydroxyurea and the RR large subunit (RRM1)-inhibitory drug gemcitabine showed little selective activity against HBV replication. In addition, osalmid also was shown to possess potent activity against a 3TC-resistant HBV strain, suggesting utility in treating drug-resistant HBV infections. Interestingly, osalmid showed synergistic effects with lamivudine (3TC) in vitro and in vivo without significant toxicity, and was shown to inhibit RR activity in vivo , thus verifying its in vivo function . Furthermore, 4-cyclopropyl-2-fluoro- N -(4-hydroxyphenyl) benzamide (YZ51), a novel derivative of osalmid, showed higher efficacy than osalmid with more potent RR inhibitory activity. These results suggest that RRM2 might be targeted for HBV inhibition, and the RRM2-targeting compound osalmid and its derivative YZ51 could be a novel class of anti-HBV candidates with potential use for hepatitis B and HBV-related HCC treatment. [ABSTRACT FROM AUTHOR]

The seismic behavior of a slope site has a critical impact on its stability and the seismic response of structures located on or near the slope. In this paper, a hybrid boundary method(HBM) is proposed for the site response analysis of slopes. Viscous and viscous-spring boundaries are applied in the HBM and equivalent loads are calculated separately on the bottom and the lateral boundary. A horizontally extended model is used to verify the HBM. The results show that the maximum error of the HBM is only 2.010%. On the ground surface of the slope site, amplification occurs at the crest side and de-amplification occurs at the toe side under various cases. The ratio of the maximum and minimum PGA on the ground surface could exceed 2. Therefore, great attention should be paid to the spatial variability of ground motion on slope sites. The HBM is also compared with four conventional approaches. The maximum errors of all the conventional approaches exceed 70%. These examples demonstrate that the HBM has much higher accuracy in practice than conventional approaches. • A hybrid boundary method(HBM) is proposed for the site response analysis of slopes. • The effectiveness and accuracy of the proposed method has been verified. • The computational accuracy of the HBM and four conventional approaches are compared. [ABSTRACT FROM AUTHOR]