Understanding U.S. regional linguistic variation with Twitter data analysis

We analyze a Big Data set of geo-tagged tweets for a year (Oct. 2013–Oct. 2014) to understand the regional linguistic variation in the U.S. Prior work on regional linguistic variations usually took a long time to collect data and focused on either rural or urban areas. Geo-tagged Twitter data offers an unprecedented database with rich linguistic representation of fine spatiotemporal resolution and continuity. From the one-year Twitter corpus, we extract lexical characteristics for twitter users by summarizing the frequencies of a set of lexical alternations that each user has used. We spatially aggregate and smooth each lexical characteristic to derive county-based linguistic variables, from which orthogonal dimensions are extracted using the principal component analysis (PCA). Finally a regionalization method is used to discover hierarchical dialect regions using the PCA components. The regionalization results reveal interesting linguistic regional variations in the U.S. The discovered regions not only confirm past research findings in the literature but also provide new insights and a more detailed understanding of very recent linguistic patterns in the U.S

Purification and In Situ Immobilization of Papain with Aqueous Two-Phase System

Papain was purified from spray-dried Carica papaya latex using aqueous two-phase system (ATPS). Then it was recovered from PEG phase by in situ immobilization or preparing cross-linked enzyme aggregates (CLEAs). The Plackett-Burman design and the central composite design (CCD) together with the response surface methodology (RSM) were used to optimize the APTS processes. The highly purified papain (96–100%) was achieved under the optimized conditions: 40% (w/w) 15 mg/ml enzyme solution, 14.33–17.65% (w/w) PEG 6000, 14.27–14.42% (w/w) NaH2PO4/K2HPO4 and pH 5.77–6.30 at 20°C. An in situ enzyme immobilization approach, carried out by directly dispersing aminated supports and chitosan beads into the PEG phase, was investigated to recover papain, in which a high immobilization yield (>90%) and activity recovery (>40%) was obtained. Moreover, CLEAs were successfully used in recovering papain from PEG phase with a hydrolytic activity hundreds times higher than the carrier-bound immobilized papain

Immunohistochemical detections of EGFR status in NSCLC

Background and objective Patients with non-small cell lung cancer (NSCLC) harboring mutations of the epidermal growth factor receptor (EGFR) respond well to EGFR-tyrosine kinase inhibitor therapy. Immunohistochemistry (IHC) is a simple and widely used technique in clinical pathology laboratories. IHC also features cost effectiveness and rapid detection of EGFR mutations compared with molecular methods. This study aims to determine the accuracy of IHC for EGFR mutation detection in NSCLC. Methods Specimens (obtained from surgery or biopsy) from 97 NSCLC cases were stained through IHC with mutation-specific antibodies. The clinicopathological features of patients with positive immunostaining results were analyzed. Positive specimens were subjected to liquid chip technology to detect the actual EGFR status. Forty NSCLC specimens obtained from surgery and confirmed to have EGFR mutations through liquid chip technology were collected. These specimens were then subjected to IHC analyses with mutation-specific antibodies. The sensitivity of IHC in detecting EGFR mutations was calculated. Results Seventeen of the 97 NSCLC specimens were stained positive, and positive results were mostly observed in females, patients with adenocarcinoma, and non-smokers. About 76.9% of specimens with positive IHC results harbored mutations. The sensitivity of IHC was 40% among the 40 cases identified as containing EGFR mutations through liquid chip technology. Conclusion The strong positive immunostaining result is accurate, but the sensitivity of the method may not be optimal and significantly varies in different studies. The widespread application of IHC in clinics must be further investigated

Influence of Immunohistochemistry Scoring Criteria in Detecting EGFR Mutations

Background and objective Appropriate immunohistochemistry (IHC) scoring criteria can guarantee the reliability of mutation detection results. Most current studies suggest that the “four-grade criterion” may be the best among all scoring systems. The aim of this study is to discuss the influence of different four-grade immunohistochemistry scoring criteria on the test results. Methods Three different four-grade immunohistochemistry scoring criteria were respectively used to evaluate the EGFR status of 83 cases of non-small cell of lung cancer (NSCLC) samples. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), the agreement of each criterion compared with the gold standard, and whether statistical significance exists between each criterion were calculated. Results No statistical difference was found among the three criteria in detecting EGFR mutations. All three criteria exhibit considerably better specificity than sensitivity. For samples with scores of “3+”, PPV could reach up to 100%. Conclusion No definite best criterion is among different four-grade scoring criteria. Regardless of the kind of criterion used, the specificity of IHC method in detecting EGFR mutations is markedly better than the sensitivity. For samples with scores of “3+”, mutation status can be confirmed, and samples can receive EGFR-TKI therapy directly

A Lightweight Neural Network for Loop Closure Detection in Indoor Visual SLAM

Abstract Loop closure detection (LCD) plays an important role in visual simultaneous location and mapping (SLAM), as it can effectively reduce the cumulative errors of the SLAM system after a long period of movement. Convolutional neural networks (CNNs) have a significant advantage in image similarity comparison, and researchers have achieved good results by incorporating CNNs into LCD. The LCD based on CNN is more robust than traditional methods. As the deep neural network frameworks from AlexNet and VGG to ResNet have become smaller while maintaining good accuracy, indoor LCD does not need robots to finish a large number of complex processing operations. To reduce the complexity of deep neural networks, this paper presents a new lightweight neural network based on MobileNet V2. We propose a strategy to use Efficient Channel Attention (ECA) to insert into Compressed MobileNet V2 (ECMobileNet) for reducing operands while maintaining precision. A corresponding loop detection method is designed based on the average distribution of ECMobileNet feature vectors combined with Euclidean distance matching. We used TUM datasets to evaluate the results, and the experimental results show that this method outperforms the state-of-the-art methods. Although the model was trained only on the indoorCVPR dataset, it also demonstrated superior performance on the TUM datasets. In particular, the proposed approach is more lightweight and highly efficient than the current existing neural network approaches. Finally, we used TUM datasets to test LCD based on ECMobileNet in PTAM, and the experimental results show that this lightweight neural network is feasible

AttnMove: History Enhanced Trajectory Recovery via Attentional Network

A considerable amount of mobility data has been accumulated due to the proliferation of location-based service. Nevertheless, compared with mobility data from transportation systems like the GPS module in taxis, this kind of data is commonly sparse in terms of individual trajectories in the sense that users do not access mobile services and contribute their data all the time. Consequently, the sparsity inevitably weakens the practical value of the data even it has a high user penetration rate. To solve this problem, we propose a novel attentional neural network-based model, named AttnMove, to densify individual trajectories by recovering unobserved locations at a fine-grained spatial-temporal resolution. To tackle the challenges posed by sparsity, we design various intra- and inter- trajectory attention mechanisms to better model the mobility regularity of users and fully exploit the periodical pattern from long-term history. We evaluate our model on two real-world datasets, and extensive results demonstrate the performance gain compared with the state-of-the-art methods. This also shows that, by providing high-quality mobility data, our model can benefit a variety of mobility-oriented down-stream applications

Theoretical Studies of the Spin-Dependent Electronic Transport Properties in Ethynyl-Terminated Ferrocene Molecular Junctions

The spin-dependent electron transport in the ferrocene-based molecular junctions, in which the molecules are 1,3-substituted and 1,3′-substituted ethynyl ferrocenes, respectively, is studied by the theoretical simulation with nonequilibrium Green’s function and density functional theory. The calculated results suggest that the substitution position of the terminal ethynyl groups has a great effect on the spin-dependent current-voltage properties and the spin filtering efficiency of the molecular junctions. At the lower bias, high spin filtering efficiency is found in 1,3′-substituted ethynyl ferrocene junction, which suggests that the spin filtering efficiency is also dependent on the bias voltage. The different spin-dependent transport properties for the two molecular junctions originate from their different evolutions of spin-up and spin-down energy levels

YAP1 Regulates the YAP1/AR/PSA Axis through Autophagy in Castration-Resistant Prostate Cancer and Mediates T-Cell Immune and Inflammatory Cytokine Infiltration

The emergence of castration-resistant prostate cancer (CRPC) following androgen deprivation therapy (ADT) is associated with increased malignancy and limited treatment options. This study aims to investigate potential connections between immune cell infiltration and inflammatory cytokines with the YAP1/AR/PSA axis by exploring their interactions with autophagy. Our research reveals heightened levels of Yes-associated protein 1 (YAP1) expression in CRPC tissues compared with tissues from androgen-dependent prostate cancer (ADPC) and benign prostate hyperplasia (BPH). Additionally, a correlation was observed between YAP1 and PSA expressions in CRPC tissues, suggesting that YAP1 may exert a regulatory influence on PSA expression within CRPC. Enhanced YAP1 expression in C4-2 cells resulted in the upregulation of androgen receptor (AR) nuclear translocation and intracellular prostate-specific antigen (PSA) levels. Conversely, the suppression of YAP1 led to a decrease in PSA expression, suggesting that YAP1 may positively regulate the PSA in castration-resistant prostate cancer (CRPC) by facilitating AR nuclear import. The modulation of the autophagy activity exerts a significant impact on the expression levels of YAP1, the AR, and the PSA. Moreover, recent advancements in immunity and inflammation studies present promising avenues for potential therapies targeting prostate cancer (PC)

The Regulatory Effect of Braided Silk Fiber Skeletons with Differential Porosities on In Vivo Vascular Tissue Regeneration and Long-Term Patency

The development of small-diameter vascular grafts that can meet the long-term patency required for implementation in clinical practice presents a key challenge to the research field. Although techniques such as the braiding of scaffolds can offer a tunable platform for fabricating vascular grafts, the effects of braided silk fiber skeletons on the porosity, remodeling, and patency in vivo have not been thoroughly investigated. Here, we used finite element analysis of simulated deformation and compliance to design vascular grafts comprised of braided silk fiber skeletons with three different degrees of porosity. Following the synthesis of low-, medium-, and high-porosity silk fiber skeletons, we coated them with hemocompatible sulfated silk fibroin sponges and then evaluated the mechanical and biological functions of the resultant silk tubes with different porosities. Our data showed that high-porosity grafts exhibited higher elastic moduli and compliance but lower suture retention strength, which contrasted with low-porosity grafts. Medium-porosity grafts offered a favorable balance of mechanical properties. Short-term in vivo implantation in rats indicated that porosity served as an effective means to regulate blood leakage, cell infiltration, and neointima formation. High-porosity grafts were susceptible to blood leakage, while low-porosity grafts hindered graft cellularization and tended to induce intimal hyperplasia. Medium-porosity grafts closely mimicked the biomechanical behaviors of native blood vessels and facilitated vascular smooth muscle layer regeneration and polarization of infiltrated macrophages to the M2 phenotype. Due to their superior performance and lack of occlusion, the medium-porosity vascular grafts were evaluated in long-term (24-months) in vivo implantation. The medium-porosity grafts regenerated the vascular smooth muscle cell layers and collagen extracellular matrix, which were circumferentially aligned and resembled the native artery. Furthermore, the formed neoarteries pulsed synchronously with the adjacent native artery and demonstrated contractile function. Overall, our study underscores the importance of braided silk fiber skeleton porosity on long-term vascular graft performance and will help to guide the design of next-generation vascular grafts