A thorough understanding of the antimicrobial mechanisms of graphene materials (GMs) is critical to the manipulation of highly efficient antimicrobial nanomaterials for future biomedical ...applications. Here we review the most recent studies of GM-mediated antimicrobial properties. This review covers the physicochemical properties of GMs, experimental surroundings, and selected microorganisms as well as the interaction between GMs and selected microorganisms to explore controversial antimicrobial activities. Finally, we rationally analyze the strengths and weaknesses of the proposed mechanisms and provide new insights into the remaining challenges and perspectives for future studies.
Terahertz (THz = 1012 Hz) radiation has attracted wide attention for its unprecedented sensing ability and its noninvasive and nonionizing properties. Tremendous strides in THz instrumentation have ...prompted impressive breakthroughs in THz biomedical research. Here, we review the current state of THz spectroscopy and imaging in various biomedical applications ranging from biomolecules, including DNA/RNA, amino acids/peptides, proteins, and carbohydrates, to cells and tissues. We also address the potential biological effects of THz radiation during its biological applications and propose future prospects for this cutting-edge technology.
We aimed to reveal clinicopathological features and explore survival-related factors of colorectal signet ring cell carcinoma (SRCC). A population-based study was carried out to investigate ...colorectal SRCC by using data extracted from the surveillance, epidemiology and end results (SEER) database between 2004 and 2015. In total, 3,278 patients with colorectal SRCC were identified, with a median age of 63 (12-103) years old. The lesions of most patients (60.49%) were located in the cecum-transverse colon. In addition, 81.27% patients had advanced clinical stage (stage III/IV), and 76.69% patients had high pathological grade. The 3-, 5-year cancer-specific survival and overall survival rate was 35.76%, 29.32% and 32.32%, 25.14%. Multivariate analysis revealed that primary site in cecum-transverse colon, married, received surgery, lymph node dissections ≥ 4 regional lymph nodes were independent favorable prognostic. Meanwhile, aged ≥ 65 years, higher grade, tumor size ˃5 cm and advanced AJCC stage were associated with poor prognosis. Patient age, tumor grade, marital status, tumor size, primary tumor location, AJCC stage, surgery and number of dissected lymph node had significant correlation with prognosis of colorectal SRCC.
Automatic modulation recognition (AMR) is a promising technology for intelligent communication receivers to detect signal modulation schemes. Recently, the emerging deep learning (DL) research has ...facilitated high-performance DL-AMR approaches. However, most DL-AMR models only focus on recognition accuracy, leading to huge model sizes and high computational complexity, while some lightweight and low-complexity models struggle to meet the accuracy requirements. This letter proposes an efficient DL-AMR model based on phase parameter estimation and transformation, with convolutional neural network (CNN) and gated recurrent unit (GRU) as the feature extraction layers, which can achieve high recognition accuracy equivalent to the existing state-of-the-art models but reduces more than a third of the volume of their parameters. Meanwhile, our model is more competitive in training time and test time than the benchmark models with similar recognition accuracy. Moreover, we further propose to compress our model by pruning, which maintains the recognition accuracy higher than 90% while has less than 1/8 of the number of parameters comparing with state-of-the-art models.
Automatic modulation recognition (AMR) plays a vital role in modern communication systems. This letter proposes a novel three-stream deep learning framework to extract the features from individual ...and combined in-phase/quadrature (I/Q) symbols of the modulated data. The proposed framework integrates one-dimensional (1D) convolutional, two-dimensional (2D) convolutional and long short-term memory (LSTM) layers to extract features more effectively from a time and space perspective. Experiments on the benchmark dataset show the proposed framework has efficient convergence speed and achieves improved recognition accuracy, especially for the signals modulated by higher dimensional schemes such as 16 quadrature amplitude modulation (16-QAM) and 64-QAM.
Mechanically alloyed AlCoCrCuFeNi high-entropy alloy (HEA) powders were used as binder to fabricate WC/HEA composites by spark plasma sintering. The effects of sintering temperature, duration time ...and binder content on microstructures and mechanical properties were studied. Compared with cobalt binder, the HEA binder has an advantage on the inhibition of WC grain growth due to the sluggish diffusion effect, and the average WC grain size decreases with increasing HEA binder content. Furthermore, the fracture toughness of WC/HEA composites firstly increases with increasing Vickers hardness and then decreases. A good comprehensive mechanical property was obtained after sintering at 1250 °C for 5 min with 10 wt.% HEA binder under a sintering pressure of 30 MPa. The Vickers hardness is 1922 HV30 and the fracture toughness is 10.41 MPa m1/2, which are higher than those of commercial WC/Co composites. Therefore, the AlCoCrCuFeNi high-entropy alloy has a potential to be a binder for WC.
•WC/AlCoCrCuFeNi high-entropy alloy composites were fabricated by SPS.•WC grain growth is inhibited effectively by AlCoCrCuFeNi binder.•The composites exhibit a good comprehensive mechanical property.•The hardness and fracture toughness decrease with increasing binder content.•Fracture toughness increases with increasing hardness first and then decreases.
The Hippo pathway plays essential roles in organ size control and cancer prevention via restricting its downstream effector, Yes‐associated protein (YAP). Previous studies have revealed an oncogenic ...function of YAP in reprogramming glucose metabolism, while the underlying mechanism remains to be fully clarified. Accumulating evidence suggests long noncoding RNAs (lncRNAs) as attractive therapeutic targets, given their roles in modulating various cancer‐related signaling pathways. In this study, we report that lncRNA breast cancer anti‐estrogen resistance 4 (BCAR4) is required for YAP‐dependent glycolysis. Mechanistically, YAP promotes the expression of BCAR4, which subsequently coordinates the Hedgehog signaling to enhance the transcription of glycolysis activators HK2 and PFKFB3. Therapeutic delivery of locked nucleic acids (LNAs) targeting BCAR4 attenuated YAP‐dependent glycolysis and tumor growth. The expression levels of BCAR4 and YAP are positively correlated in tissue samples from breast cancer patients, where high expression of both BCAR4 and YAP is associated with poor patient survival outcome. Taken together, our study not only reveals the mechanism by which YAP reprograms glucose metabolism, but also highlights the therapeutic potential of targeting YAP‐BCAR4‐glycolysis axis for breast cancer treatment.
Synopsis
Yes‐associated protein promotes cancer formation by reprogramming glucose metabolism. A long noncoding RNA BCAR4 is a key downstream effector of YAP, in regulation of glycolysis and tumorigenesis via GLI2‐mediated expression of key glycolytic enzymes.
BCAR4 is a direct transcriptional target of YAP.
BCAR4 promotes glycolysis by increasing the expression of HK2 and PFKFB3.
GLI2 activation is required for the expression of glycolytic enzymes downstream of BCAR4
High YAP and BCAR4 expression levels positively correlate in breast cancer patient samples and are linked to poor clinical outcomes.
Inhibition of BCAR4 via Locked Nucleic Acids (LNAs) attenuated YAP‐dependent glycolysis and tumor growth.
Yes‐associated protein activation triggers transcription of long noncoding RNA BCAR4, leading to GLI2‐mediated expression of key glycolytic enzymes.
The coherent interaction between quantum emitters and photonic modes in cavities underlies many of the current strategies aiming at generating and controlling photonic quantum states. A plasmonic ...nanocavity provides a powerful solution for reducing the effective mode volumes down to nanometre scale, but spatial control at the atomic scale of the coupling with a single molecular emitter is challenging. Here we demonstrate sub-nanometre spatial control over the coherent coupling between a single molecule and a plasmonic nanocavity in close proximity by monitoring the evolution of Fano lineshapes and photonic Lamb shifts in tunnelling electron-induced luminescence spectra. The evolution of the Fano dips allows the determination of the effective interaction distance of ∼1 nm, coupling strengths reaching ∼15 meV and a giant self-interaction induced photonic Lamb shift of up to ∼3 meV. These results open new pathways to control quantum interference and field-matter interaction at the nanoscale.
Background
The usefulness of 3D deep learning‐based classification of breast cancer and malignancy localization from MRI has been reported. This work can potentially be very useful in the clinical ...domain and aid radiologists in breast cancer diagnosis.
Purpose
To evaluate the efficacy of 3D deep convolutional neural network (CNN) for diagnosing breast cancer and localizing the lesions at dynamic contrast enhanced (DCE) MRI data in a weakly supervised manner.
Study Type
Retrospective study.
Subjects
A total of 1537 female study cases (mean age 47.5 years ±11.8) were collected from March 2013 to December 2016. All the cases had labels of the pathology results as well as BI‐RADS categories assessed by radiologists.
Field Strength/Sequence
1.5 T dynamic contrast‐enhanced MRI.
Assessment
Deep 3D densely connected networks were trained under image‐level supervision to automatically classify the images and localize the lesions. The dataset was randomly divided into training (1073), validation (157), and testing (307) subsets.
Statistical Tests
Accuracy, sensitivity, specificity, area under receiver operating characteristic curve (ROC), and the McNemar test for breast cancer classification. Dice similarity for breast cancer localization.
Results
The final algorithm performance for breast cancer diagnosis showed 83.7% (257 out of 307) accuracy (95% confidence interval CI: 79.1%, 87.4%), 90.8% (187 out of 206) sensitivity (95% CI: 80.6%, 94.1%), 69.3% (70 out of 101) specificity (95% CI: 59.7%, 77.5%), with the area under the curve ROC of 0.859. The weakly supervised cancer detection showed an overall Dice distance of 0.501 ± 0.274.
Data Conclusion
3D CNNs demonstrated high accuracy for diagnosing breast cancer. The weakly supervised learning method showed promise for localizing lesions in volumetric radiology images with only image‐level labels.
Level of Evidence: 4
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2019;50:1144–1151.
Actinomycetes are outstanding and fascinating sources of potent bioactive compounds, particularly antibiotics. In recent years, rare actinomycetes have had an increasingly important position in the ...discovery of antibacterial compounds, especially
Micromonospora
,
Actinomadura
and
Amycolatopsis
. Focusing on the period from 2008 to 2018, we herein summarize the structures and bioactivities of secondary metabolites from rare actinomycetes, involving 21 genera.
A detailed introduction to the structures and bioactivities of secondary metabolites from rare actinomycetes is made.
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