Hemodynamic analysis of thoracic endovascular aortic repair with left subclavian artery reconstructed by chimney stent.

OBJECTIVES: The purpose of this study was to investigate the hemodynamic consequences of thoracic endovascular aortic repair which reconstructed left subclavian artery by chimney stent (ch-TEVAR). METHODS: Two patients who underwent thoracic endovascular aortic repair (TEVAR) and left subclavian artery (LSA) reconstruction using chimney stents were selected. Preoperative and postoperative CTA images were collected to reconstruct hemodynamic models for comparing and analyzing blood pressure, blood flow velocity, and wall shear stress in the aortic arch and its major branches. Concurrently, morphological alterations and position of chimney stent were also assessed. RESULTS: After the reconstruction of LSA in ch-TEVAR, no endoleak was seen, but the stent in LSA was compressed. The blood flow velocity of the LSA increased and disordered, the pressure was reduced, and the WSS was increased. Even more, there were a large amount of turbulence found in the LSA of one case, and its LSA was blocked. CONCLUSION: Chimney stent reduces the occurrence of endoleak due to its excellent deformation ability, but the compressed stent has a greater impact on the hemodynamics of LSA and eventually leads to LSA occlusion; in order to keep the LSA unobstructed, it is necessary to pay attention to the position of the chimney stent and keep it straight and do not fold or twist. Chimney stent has little influence on the aortic arch and the rest of the aortic arch branches.

A Localized High-Concentration Water/Organic Hybrid Electrolyte for 2.5 V Li4Ti5O12/LiMn2O4 Batteries.

The "solvent-in-salt" electrolytes for an aqueous system, including "water-in-salt" electrolytes and "bisolvent-in-salt" electrolytes, have shown significantly improved electrochemical stability toward low-voltage anodes and high-voltage cathodes. However, the heavy use of salt raises concerns of high cost, high viscosity, inferior wettability, and poor low-temperature performance. Herein, a "localized bisolvent-in-salt electrolyte" is proposed by introducing 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether (TTE) as the diluent to the high-concentration water/sulfolane hybrid (BSiS-SL) electrolytes, forming a ternary solvent-based electrolyte, Li(H2O)0.9SL1.3·TTE1.3 (HS-TTE). The introduction of TTE dilutes the compact ionic clusters, while the original primary Li+ solvation structure remains, and in the meantime, boosts the formation of a robust solid electrolyte interphase. As a result, a wide electrochemically stable window of 4.4 V is achieved. In comparison with the bisolvent BSiS-SL system, the trisolvent HS-TTE electrolyte exhibits a low salt concentration of 2.1 mol kg-1, resulting in drastically reduced viscosity, superb separator wettability, and largely improved low-temperature performance. The constructed 2.5 V Li4Ti5O12/LiMn2O4 cell shows an excellent capacity retention of 80.7% after 800 cycles, and the cell can even work at -30 °C. With these extraordinary advantages, the fundamental designing strategy of the HS-TTE electrolyte developed in this work can promote the practical applications of solvent-in-salt electrolytes.

Toward the High-Performance Lithium Primary Batteries by Chemically Modified Fluorinate Carbon with δ-MnO2.

Li/CFx battery is one of the most promising lithium primary batteries (LPBs) which yields the highest energy density but with poor rate capability. This Achilles'' heel hinders the large-scale applications of Li/CFx batteries. This work first reports a facile chemical modification method of CFx with δ-MnO2 . Having benefited from the chemical bonding, the electrochemical performance at high-rate discharge is remarkably enhanced without compromising the specific capacity. The coin cells exhibit an energy density of 1.94 × 103  Wh kg-1 at 0.2 C, which is approaching the theoretical energy density of commercial fluorinated graphite (2.07 × 103  Wh kg-1 ). A power density of 5.49 × 104  W kg-1 at 40 C associated with an energy density of 4.39 × 102  Wh kg-1 , which is among the highest value of Li/CFx batteries, are obtained. Besides, the punch batteries achieve an ultrahigh power density of 4.39 × 104  W kg-1 with an energy density of 7.60 × 102  Wh kg-1 at 30 C. The intrinsic reasons for this outstanding electrochemical performance, which are known as the fast Li+ diffusion kinetics guided by thin δ-MnO2 flakes and the low formation energy barrier caused by chemical bonding, are explored by the galvanostatic intermittent titration technique (GITT) and theoretical calculations.

ATFE-Net: Axial Transformer and Feature Enhancement-based CNN for ultrasound breast mass segmentation.

Breast mass is one of the main clinical symptoms of breast cancer. Recently, many CNN-based methods for breast mass segmentation have been proposed. However, these methods have difficulties in capturing long-range dependencies, causing poor segmentation of large-scale breast masses. In this paper, we propose an axial Transformer and feature enhancement-based CNN (ATFE-Net) for ultrasound breast mass segmentation. Specially, an axial Transformer (Axial-Trans) module and a Transformer-based feature enhancement (Trans-FE) module are proposed to capture long-range dependencies. Axial-Trans module only calculates self-attention in width and height directions of input feature maps, which reduces the complexity of self-attention significantly from O(n2) to O(n). In addition, Trans-FE module can enhance feature representation by capturing dependencies between different feature layers, since deeper feature layers have richer semantic information and shallower feature layers have more detailed information. The experimental results show that our ATFE-Net achieved better performance than several state-of-the-art methods on two publicly available breast ultrasound datasets, with Dice coefficient of 82.46% for BUSI and 86.78% for UDIAT, respectively.

Vertebral artery course variation leading to an insufficient proximal anchoring area for thoracic endovascular aortic repair.

BACKGROUNDS: We aimed to demonstrate the feasibility of thoracic endovascular aortic repair for type B aortic dissection in patients with an insufficient proximal anchoring area due to the vertebral artery originating from the aortic arch. METHODS: In this study, we report two patients with type B aortic dissection who were complicated with left vertebral artery course variation. Specifically, the left vertebral artery originated from the aortic arch. In these patients, the anchoring area (<15 mm) was not sufficient between the left vertebral artery and the ruptured aortic dissection. RESULT: We reconstructed the left vertebral artery during horacic endovascular aortic repair. Both patients recovered well and were discharged without any adverse events. CONCLUTION: Our experience shows that horacic endovascular aortic repair is feasible in patients with type B aortic dissection who have an insufficient proximal anchoring area due to the left vertebral artery originating from the aortic arch.

Learning multi-frequency features in convolutional network for mammography classification.

Breast cancer is a common life-threatening disease among women. Computer-aided methods can provide second opinion or decision support for early diagnosis in mammography images. However, the whole images classification is highly challenging due to small sizes of lesion and slow contrast between lesions and fibro-glandular tissue. In this paper, inspired by conventional machine learning methods, we present a Multi Frequency Attention Network (MFA-Net) to highlight the salient features. The network decomposes the features into low spatial frequency components and high spatial frequency components, and then recalibrates discriminating features based on two-dimensional Discrete Cosine Transform in two different frequency parts separately. Low spatial frequency features help determine if there is a tumor while high spatial frequency features help focus more on the margin of the tumor. Our studies empirically show that compared to traditional convolutional neural network (CNN), the proposed method mitigates the influence of the margin of pectoral muscle and breast in mammography, which brings significant improvement. For malignant and benign classification, by using transfer learning, the proposed MFA-Net achieves the AUC index 91.71% on the INbreast dataset.

FS-UNet: Mass segmentation in mammograms using an encoder-decoder architecture with feature strengthening.

Breast mass segmentation in mammograms is still a challenging and clinically valuable task. In this paper, we propose an effective and lightweight segmentation model based on convolutional neural networks to automatically segment breast masses in whole mammograms. Specifically, we first developed feature strengthening modules to enhance relevant information about masses and other tissues and improve the representation power of low-resolution feature layers with high-resolution feature maps. Second, we applied a parallel dilated convolution module to capture the features of different scales of masses and fully extract information about the edges and internal texture of the masses. Third, a mutual information loss function was employed to optimise the accuracy of the prediction results by maximising the mutual information between the prediction results and the ground truth. Finally, the proposed model was evaluated on both available INbreast and CBIS-DDSM datasets, and the experimental results indicated that our method achieved excellent segmentation performance in terms of dice coefficient, intersection over union, and sensitivity metrics.

DCANet: Dual contextual affinity network for mass segmentation in whole mammograms.

PURPOSE: Breast mass segmentation in mammograms remains a crucial yet challenging topic in computer-aided diagnosis systems. Existing algorithms mainly used mass-centered patches to achieve mass segmentation, which is time-consuming and unstable in clinical diagnosis. Therefore, we aim to directly perform fully automated mass segmentation in whole mammograms with deep learning solutions. METHODS: In this work, we propose a novel dual contextual affinity network (a.k.a., DCANet) for mass segmentation in whole mammograms. Based on the encoder-decoder structure, two lightweight yet effective contextual affinity modules including the global-guided affinity module (GAM) and the local-guided affinity module (LAM) are proposed. The former aggregates the features integrated by all positions and captures long-range contextual dependencies, aiming to enhance the feature representations of homogeneous regions. The latter emphasizes semantic information around each position and exploits contextual affinity based on the local field-of-view, aiming to improve the indistinction among heterogeneous regions. RESULTS: The proposed DCANet is greatly demonstrated on two public mammographic databases including the DDSM and the INbreast, achieving the Dice similarity coefficient (DSC) of 85.95% and 84.65%, respectively. Both segmentation performance and computational efficiency outperform the current state-of-the-art methods. CONCLUSION: According to extensive qualitative and quantitative analyses, we believe that the proposed fully automated approach has sufficient robustness to provide fast and accurate diagnoses for possible clinical breast mass segmentation.

Docosahexaenoic acid inhibits vascular smooth muscle cell migration and proliferation by decreasing microRNA­155 expression levels.

Vascular smooth muscle cell (VSMC) hyperplasia is a common cause of carotid restenosis. In the present study, the potential protective effects of docosahexaenoic acid (DHA) in carotid restenosis and the underlying mechanism of its effects were examined. VSMCs were treated with DHA, a polyunsaturated ω­3 fatty acid. Cell migration and proliferation were assessed using wound healing and Cell Counting Kit­8 assays and by measuring Ki­67 protein levels. Additionally, the expression levels of microRNA­155 were determined by reverse transcription­quantitative PCR (RT­qPCR). The involvement of microRNA­155 in the regulation of migration and proliferation was evaluated by transfecting VSMCs with microRNA mimics and inhibitors. Moreover, the reversal of migration and proliferation after transfection of VSMCs with the microRNA mimics and subsequent treatment with DHA was investigated. A target gene of microRNA­155 was identified using RT­qPCR and luciferase assays. The migration and proliferation of VSMCs, as well as the expression of microRNA­155 was inhibited by DHA stimulation. MicroRNA­155 regulated the migration and proliferation of VSMCs. Finally, proliferation and migration of VSMCs were reduced following DHA treatment, which was mediated by an increase in the expression levels of microRNA­155. Suppressor of cytokine signalling 1 (Socs1) was the target gene of microRNA­155. In conclusion, DHA inhibited VSMC migration and proliferation by reducing microRNA­155 expression. This effect may be caused by the microRNA­155 target gene Socs1.

Acetylshikonin attenuates angiotensin II-induced proliferation and motility of human brain smooth muscle cells by inhibiting Wnt/ß-catenin signaling.

Cerebrovascular smooth muscle cell proliferation and migration contribute to hyperplasia in case of cerebrovascular remodeling and stroke. In the present study, we investigated the effects of acetylshikonin, the main ingredient of a Chinese traditional medicine Zicao, on human brain vascular smooth muscle cell (HBVSMCs) proliferation and migration induced by angiotensin II (AngII), and the underlying mechanisms. We found that acetylshikonin treatment significantly inhibited AngII-induced HBVSMCs proliferation and cell cycle transition from G1 to S phase. Wound-healing assay and Transwell assay showed that AngII-induced cell migration and invasion were markedly attenuated by acetylshikonin. In addition, AngII challenge significantly induced Wnt/ß-catenin signaling activation, as evidenced by increased ß-catenin phosphorylation and nuclear translocation and GSK-3ß phosphorylation. However, acetylshikonin treatment inhibited the activation of Wnt/ß-catenin signaling. Consequently, western blotting analysis revealed that acetylshikonin effectively reduced the expression of downstream target genes in AngII-treated cells, including c-myc, survivin and cyclin D1, which contributed to the inhibitory effect of acetylshikonin on HBVSMCs proliferation. Further, stimulation with recombinant Wnt3a dramatically reversed acetylshikonin-mediated inhibition of proliferation and cell cycle transition in HBVSMCs. Our study demonstrates that acetylshikonin prevents AngII-induced cerebrovascular smooth muscle cells proliferation and migration through inhibition of Wnt/ß-catenin pathway, indicating that acetylshikonin may present a potential option for the treatment of cerebrovascular remodeling.

Metabolomics Analysis for Defining Serum Biochemical Markers in Colorectal Cancer Patients with Qi Deficiency Syndrome or Yin Deficiency Syndrome.

Colorectal cancer is one of the leading causes of tumor-associated death, and traditional Chinese medicine (TCM) classifies colorectal cancer into various subtypes mainly according to the symptomatic pattern identification (ZHENG). Here, we investigated the difference in metabolic profiles of serum by comparing colorectal cancer subjects with Nondeficiency (ND), Qi deficiency (QD), and Yin deficiency (YD). The ratio of subjects with carcinoembryonic antigen (CEA) was higher in YD pattern, and the ratio of subjects with carbohydrate antigen 19-9 (CA19-9) was higher both in YD and in QD, compared with ND. As a result of metabolomics analysis, twenty-five metabolites displayed differences between QD and ND, while twenty-eight metabolites displayed differences between YD and ND. The downregulated metabolites in QD/ND and YD/ND mainly include carbohydrates and the upregulated metabolites mainly include amino acids and fatty acids, suggesting conversion obstruction of carbohydrates, fatty acids, and amino acids occurs in patients with QD and YD compared with ND. Our results demonstrate that colorectal cancer patients with QD or YD were associated with metabolic disorders and the variations of serum metabolic profiles may serve as potential biochemical markers for diagnosis and prognosis of colorectal cancer patients displayed QD or YD patterns.

The fundamental theory of traditional Chinese medicine and the consideration in its research strategy.

Stressing the uniqueness and complexity of traditional Chinese medicine (TCM) theory system, this paper analyzes the characteristics of TCM as a discipline from four perspectives: scientific nature, fundamental theory, clinical practice, and pharmacological action. It suggests that when the research strategy of TCM theory is designed, the core theory of TCM should be emphasized on the theoretical research on TCM original thinking theory, TCM theory, Chinese materia medica and formulas, acupuncture and moxibustion, meridians and collaterals, and other related fields. Researchers and practitioners should ensure that the basic research on TCM theory is based on clinical practice, research methods (both traditional and contemporary) are exploited, and methodological innovation is underscored. The rule of TCM development should be followed and the characteristics and advantages of TCM carried forward. Meanwhile, the methods and theory of contemporary science and technology should be exploited to fulfill the goal of inheriting, enriching, and developing the fundamental theory of TCM.