Sorafenib is an oral multikinase inhibitor that suppresses tumor cell proliferation and angiogenesis and promotes tumor cell apoptosis It was approved by the FDA for the treatment of advanced renal ...cell carcinoma in 2006, and as a unique target drug for advanced hepatocellular carcinoma （HCC） in 2007. Sorafenib can significantly extend the median survival time of patients but only by 3-5 months. Moreover, it is associated with serious adverse side effects, and drug resistance often develops. Therefore, it is of great importance to explore the mechanisms underlying sorafenib resistance and to develop individualized therapeutic strategies for coping with these problems. Recent studies to the primary resistance, mechanisms are underying the acquired resistance to sorafenib, such as crosstalk involving PI3K/Akt and JAK-STAT pathways, the activation of hypoxia-inducible pathways, and epithelial-mesenchymal transition. Here, we briefly describe the function of sorafenib, its clinical application, and the molecular mechanisms for drug resistance, especially for HCC patients.
A robust automatic micro-expression recognition system would have broad applications in national safety, police interrogation, and clinical diagnosis. Developing such a system requires high quality ...databases with sufficient training samples which are currently not available. We reviewed the previously developed micro-expression databases and built an improved one (CASME II), with higher temporal resolution (200 fps) and spatial resolution (about 280×340 pixels on facial area). We elicited participants' facial expressions in a well-controlled laboratory environment and proper illumination (such as removing light flickering). Among nearly 3000 facial movements, 247 micro-expressions were selected for the database with action units (AUs) and emotions labeled. For baseline evaluation, LBP-TOP and SVM were employed respectively for feature extraction and classifier with the leave-one-subject-out cross-validation method. The best performance is 63.41% for 5-class classification.
The hypothalamus regulates innate social interactions, but how hypothalamic neurons transduce sex-related sensory signals emitted by conspecifics to trigger appropriate behaviors remains unclear. ...Here, we addressed this issue by identifying specific hypothalamic neurons required for sensing conspecific male cues relevant to inter-male aggression. By in vivo recording of neuronal activities in behaving mice, we showed that neurons expressing dopamine transporter (DAT+) in the ventral premammillary nucleus (PMv) of the hypothalamus responded to male urine cues in a vomeronasal organ (VNO)-dependent manner in naive males. Retrograde trans-synaptic tracing further revealed a specific group of neurons in the bed nucleus of the stria terminalis (BNST) that convey male-relevant signals from VNO to PMv. Inhibition of PMvDAT+ neurons abolished the preference for male urine cues and reduced inter-male attacks, while activation of these neurons promoted urine marking and aggression. Thus, PMvDAT+ neurons exemplify a hypothalamic node that transforms sex-related chemo-signals into recognition and behaviors.
•PMvDAT+ neurons selectively tune to gonad-intact conspecific male urine cues•v-BNST relay male-relevant chemosensory information from VNO to PMvDAT+ neurons•Inhibition of PMvDAT+ neurons blocks male urine preference and decreases attack•Activation of PMvDAT+ neurons promotes urine marking and aggression
How hypothalamic neurons transduce sex signals emitted by conspecifics to trigger appropriate behavioral outputs remains unclear. Chen et al. identify PMvDAT+ neurons as a key node that extract male-relevant information from the chemosensory pathway, via the v-BNST, to coordinate multiple behavioral responses, including male urine preference, inter-male aggression, and urine marking.
Nanoscale robots have potential as intelligent drug delivery systems that respond to molecular triggers. Using DNA origami we constructed an autonomous DNA robot programmed to transport payloads and ...present them specifically in tumors. Our nanorobot is functionalized on the outside with a DNA aptamer that binds nucleolin, a protein specifically expressed on tumor-associated endothelial cells, and the blood coagulation protease thrombin within its inner cavity. The nucleolin-targeting aptamer serves both as a targeting domain and as a molecular trigger for the mechanical opening of the DNA nanorobot. The thrombin inside is thus exposed and activates coagulation at the tumor site. Using tumor-bearing mouse models, we demonstrate that intravenously injected DNA nanorobots deliver thrombin specifically to tumor-associated blood vessels and induce intravascular thrombosis, resulting in tumor necrosis and inhibition of tumor growth. The nanorobot proved safe and immunologically inert in mice and Bama miniature pigs. Our data show that DNA nanorobots represent a promising strategy for precise drug delivery in cancer therapy.
This article investigates the problem of attack detection of false data injection attacks for a class of large-scale smart grid systems in the context of cyber-physical systems. First, by exploiting ...the graph theory to decompose the considered system into multiple interconnected subsystems, a bank of dynamic reduced-order observers are delicately constructed to generate residual signals for the attack detection task. Then, a novel decentralized attack detection scheme is proposed based on the adaptive detection thresholds with prescribed performance. Compared with the existing results, the proposed detection scheme has less conservative thresholds and enhanced robustness against process disturbance and measurement noise, such that the detectability is improved. Finally, the effectiveness and availability of the proposed scheme are verified by two simulation examples and the experimental results from IEEE 30-bus system built in the OPAL-RT real-time simulator.
Micro-expressions are brief facial movements characterized by short duration, involuntariness and low intensity. Recognition of spontaneous facial micro-expressions is a great challenge. In this ...paper, we propose a simple yet effective Main Directional Mean Optical-flow (MDMO) feature for micro-expression recognition. We apply a robust optical flow method on micro-expression video clips and partition the facial area into regions of interest (ROIs) based partially on action units. The MDMO is a ROI-based, normalized statistic feature that considers both local statistic motion information and its spatial location. One of the significant characteristics of MDMO is that its feature dimension is small. The length of a MDMO feature vector is 36 × 2 = 72, where 36 is the number of ROIs. Furthermore, to reduce the influence of noise due to head movements, we propose an optical-flow-driven method to align all frames of a micro-expression video clip. Finally, a SVM classifier with the proposed MDMO feature is adopted for micro-expression recognition. Experimental results on three spontaneous micro-expression databases, namely SMIC, CASME and CASME II, show that the MDMO can achieve better performance than two state-of-the-art baseline features, i.e., LBP-TOP and HOOF.
Purpose
Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) ...and deep learning based on CT images to predict MVI preoperatively.
Methods
In total, 405 patients were included. A total of 7302 radiomic features and 17 radiological features were extracted by a radiomics feature extraction package and radiologists, respectively. We developed a XGBoost model based on radiomics features, radiological features and clinical variables and a three-dimensional convolutional neural network (3D-CNN) to predict MVI status. Next, we compared the efficacy of the two models.
Results
Of the 405 patients, 220 (54.3%) were MVI positive, and 185 (45.7%) were MVI negative. The areas under the receiver operating characteristic curves (AUROCs) of the Radiomics-Radiological-Clinical (RRC) Model and 3D-CNN Model in the training set were 0.952 (95% confidence interval (CI) 0.923–0.973) and 0.980 (95% CI 0.959–0.993), respectively (
p
= 0.14). The AUROCs of the RRC Model and 3D-CNN Model in the validation set were 0.887 (95% CI 0.797–0.947) and 0.906 (95% CI 0.821–0.960), respectively (
p
= 0.83). Based on the MVI status predicted by the RRC and 3D-CNN Models, the mean recurrence-free survival (RFS) was significantly better in the predicted MVI-negative group than that in the predicted MVI-positive group (RRC Model: 69.95 vs. 24.80 months,
p
< 0.001; 3D-CNN Model: 64.06 vs. 31.05 months,
p
= 0.027).
Conclusion
The RRC Model and 3D-CNN models showed considerable efficacy in identifying MVI preoperatively. These machine learning models may facilitate decision-making in HCC treatment but requires further validation.
Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices ...whose product closely approximates the original matrix. Traditional NMF methods minimize either the l2 norm or the Kullback-Leibler distance between the product of the two matrices and the original matrix. Correntropy was recently shown to be an effective similarity measurement due to its stability to outliers or noise.
We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering. Instead of minimizing the l2 norm or the Kullback-Leibler distance, NMF-MCC maximizes the correntropy between the product of the two matrices and the original matrix. The optimization problem can be solved by an expectation conditional maximization algorithm.
Extensive experiments on six cancer benchmark sets demonstrate that the proposed method is significantly more accurate than the state-of-the-art methods in cancer clustering.
•Dual-frequency ultrasound thawing (DUT) was used to treated small yellow croaker.•The small yellow croaker treated by DUT exhibited satisfactory quality traits.•The quality of the fish was evaluated ...by TMT-labeled quantitative proteomics.•There were 40 proteins correlated closely with quality indicators of the fish meat.•Eleven proteins can be potential biomarkers for monitoring quality of the fish.
The effect of dual-frequency sequential ultrasonic thawing (DUT) on the quality of quick-frozen small yellow croaker was studied by TMT-labeled quantitative proteomic method. A total number of 75 proteins were identified as differentially abundant proteins (DAPs) in fish meat treated by DUT, while 72 DAPs were in flow water thawing (FWT). The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis indicated that the DAPs in the significant enrichment pathway of DUT group were enzymes. Compared with FWT, DUT had a significant effect on the enzyme content. The correlation analyses indicated that 40 DAPs were related with the quality traits. The 11 highly correlated DAPs are expected to be used as potential protein markers for texture profile analyses, color, thawing loss, water-holding capacity, and pH of thawed small yellow croaker quality. These results provide a further understanding of the quality stability of quick-frozen small yellow croaker treated by the DUT.
Magnesium rechargeable batteries potentially offer high-energy density, safety, and low cost due to the ability to employ divalent, dendrite-free, and earth-abundant magnesium metal anode. Despite ...recent progress, further development remains stagnated mainly due to the sluggish scission of magnesium-chloride bond and slow diffusion of divalent magnesium cations in cathodes. Here we report a battery chemistry that utilizes magnesium monochloride cations in expanded titanium disulfide. Combined theoretical modeling, spectroscopic analysis, and electrochemical study reveal fast diffusion kinetics of magnesium monochloride cations without scission of magnesium-chloride bond. The battery demonstrates the reversible intercalation of 1 and 1.7 magnesium monochloride cations per titanium at 25 and 60 °C, respectively, corresponding to up to 400 mAh g
capacity based on the mass of titanium disulfide. The large capacity accompanies with excellent rate and cycling performances even at room temperature, opening up possibilities for a variety of effective intercalation hosts for multivalent-ion batteries.Magnesium rechargeable batteries potentially offer high-energy density, safety, and low cost. Here the authors show a battery that reversibly intercalates magnesium monochloride cations with excellent rate and cycle performances in addition to the large capacity.
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