ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Mechanism of piR-1245/PIWI-like protein-2 regulating Janus kinase-2/signal transducer and activator of transcription-3/vascular endothelial growth factor signaling pathway in retinal neovascularization

Inhibiting retinal neovascularization is the optimal strategy for the treatment of retina-related diseases, but there is currently no effective treatment for retinal neovascularization. P-element-induced wimpy testis (PIWI)-interacting RNA (piRNA) is a type of small non-coding RNA implicated in a variety of diseases. In this study, we found that the expression of piR-1245 and the interacting protein PIWIL2 were remarkably increased in human retinal endothelial cells cultured in a hypoxic environment, and cell apoptosis, migration, tube formation and proliferation were remarkably enhanced in these cells. Knocking down piR-1245 inhibited the above phenomena. After intervention by a p-JAK2 activator, piR-1245 decreased the expression of hypoxia inducible factor-1α and vascular endothelial growth factor through the JAK2/STAT3 pathway. For in vivo analysis, 7-day-old newborn mice were raised in 75 ± 2% hyperoxia for 5 days and then piR-1245 in the retina was knocked down. In these mice, the number of newly formed vessels in the retina was decreased, the expressions of inflammation-related proteins were reduced, the number of apoptotic cells in the retina was decreased, the JAK2/STAT3 pathway was inhibited, and the expressions of hypoxia inducible factor-1α and vascular endothelial growth factor were decreased. Injection of the JAK2 inhibitor JAK2/TYK2-IN-1 into the vitreous cavity inhibited retinal neovascularization in mice and reduced expression of hypoxia inducible factor-1α and vascular endothelial growth factor. These findings suggest that piR-1245 activates the JAK2/STAT3 pathway, regulates the expression of hypoxia inducible factor-1α and vascular endothelial growth factor, and promotes retinal neovascularization. Therefore, piR-1245 may be a new therapeutic target for retinal neovascularization.
Geometrically programmed self-limited assembly of tubules using DNA origami colloids

Self-assembly is one of the most promising strategies for making functional materials at the nanoscale, yet new design principles for making self-limiting architectures, rather than spatially unlimited periodic lattice structures, are needed. To address this challenge, we explore the tradeoffs between addressable assembly and self-closing assembly of a specific class of self-limiting structures: cylindrical tubules. We make triangular subunits using DNA origami that have specific, valence-limited interactions and designed binding angles, and we study their assembly into tubules that have a self-limited width that is much larger than the size of an individual subunit. In the simplest case, the tubules are assembled from a single component by geometrically programming the dihedral angles between neighboring subunits. We show that the tubules can reach many micrometers in length and that their average width can be prescribed through the dihedral angles. We find that there is a distribution in the width and the chirality of the tubules, which we rationalize by developing a model that considers the finite bending rigidity of the assembled structure as well as the mechanism of self-closure. Finally, we demonstrate that the distributions of tubules can be further sculpted by increasing the number of subunit species, thereby increasing the assembly complexity, and demonstrate that using two subunit species successfully reduces the number of available end states by half. These results help to shed light on the roles of assembly complexity and geometry in self-limited assembly and could be extended to other self-limiting architectures, such as shells, toroids, or triply periodic frameworks.
The Effectiveness of an Oral Fixed-Dose Combination of Netupitant and Palonosetron (NEPA) in Patients With Multiple Risk Factors for Chemotherapy-Induced Nausea and Vomiting: A Multicenter, Observational Indian Study

Background Female gender, young age, first chemotherapy cycle, and low alcohol intake have all been linked to an increased risk of nausea and vomiting from chemotherapy. We intended to see if netupitant and palonosetron (NEPA) could prevent chemotherapy-induced nausea and vomiting (CINV) in patients with risk factors such as age, gender, chemotherapy cycle number, and alcohol consumption history. Methods In this retrospective study, chemotherapy-naïve patients who were prescribed netupitant (300 mg) and palonosetron (0.50 mg) (NEPA) before the first cycle of chemotherapy were analyzed for overall, acute, and delayed phases of complete response (CR), complete protection (CP), and control. Results In the acute phase (AP), delayed phase (DP), and overall phase (OP), complete response was 88.23%, 86.27%, and 86.27%, respectively; complete protection was 80.39%, 78.43%, and 76.47%, respectively; and complete control was 76.47%, 72.54%, and 70.58%, respectively, in the whole population (i.e., 51 patients). Complete response, protection, and control in the overall phase were achieved by 86.27%, 72.72%, and 68.18% of patients who received the highly emetogenic chemotherapy (HEC) regimen (i.e., 44 patients), respectively. Conclusion NEPA provided a consistent magnitude of benefit for patients who are at high risk, receiving HEC and moderately emetogenic chemotherapy (MEC), and having good control in the acute, delayed, and overall phases of CINV.
A Generic Interface Enabling Combinations of State-of-the-Art Path Planning and Tracking Algorithms

In the development of Level 4 automated driving functions, very specific, but diverse, requirements with respect to the operational design domain have to be considered. In order to accelerate this development, it is advantageous to combine dedicated state-of-the-art software components, as building blocks in modular automated driving function architectures, instead of developing special solutions from scratch. However, e.g., in local motion planning and control, the combination of components is still limited in practice, due to necessary interface alignments, which might yield sub-optimal solutions and additional development overhead. The application of generic interfaces, which manage the data transfer between the software components, has the potential to avoid these drawbacks and hence, to further boost this development approach. This publication contributes such a generic interface concept between the local path planning and path tracking systems. The crucial point is a generalization of the lateral tracking error computation, based on an introduced error classification. It substantiates the integration of an internal reference path representation into the interface, to resolve the component interdependencies. The resulting, proposed interface enables arbitrary combinations of components from a comprehensive set of state-of-the-art path planning and tracking algorithms. Two interface implementations are finally applied in an exemplary automated driving function assembly task.
Positive and Negative Label Propagations

This paper extends the state-of-the-art label propagation (LP) framework in the propagation of negative labels. More specifically, the state-of-the-art LP methods propagate information of the form "thesample i should be assigned the label k." The proposed method extends the state-of-the-art framework by considering additional information of the form "the sample i should not be assigned the label k." A theoretical analysis is presented in order to include negative LP in the problem formulation. Moreover, a method for selecting the negative labels in cases when they are not inherent from the data structure is presented. Furthermore, the incorporation of negative label information in two multigraph LP methods is presented. Finally, a discussion on the proposed algorithm extension to out of sample data, as well as scalability issues, is presented. Experimental results in various scenarios showed that the incorporation of negative label information increases, in all cases, the classification accuracy of the state of the art.
QML-Based Joint Diagonalization of Positive-Definite Hermitian Matrices

In this paper, a new algorithm for approximate joint diagonalization (AJD) of positive-definite Hermitian matrices is presented. The AJD matrix, which is assumed to be square non-unitary, is derived via minimization of a quasi-maximum likelihood (QML) objective function. This objective function coincides asymptotically with the maximum likelihood (ML) objective function, hence enabling the proposed algorithm to asymptotically approach the ML estimation performance. In the proposed method, the rows of the AJD matrix are obtained independently, in an iterative manner. This feature enables direct estimation of full row-rank rectangular AJD sub-matrices. Under some mild assumptions, convergence of the proposed algorithm is asymptotically guarantied, such that the error norm corresponding to each row of the AJD matrix reduces significantly after the first iteration, and the convergence is almost Q-super linear. This property results rapid convergence, which leads to low computational load in the proposed method. The performance of the proposed algorithm is evaluated and compared to other state-of-the-art algorithms for AJD and its practical use is demonstrated in the blind source separation and blind source extraction problems. The results imply that under the assumptions of high signal-to-noise ratio and large amount of matrices, the proposed algorithm is computationally efficient with performance similar to state-of-the-art algorithms for AJD.
Fungal assisted bio-treatment of environmental pollutants with comprehensive emphasis on noxious heavy metals: Recent updates

In the present time of speedy developments and industrialization, heavy metals are being uncovered in aquatic environment and soil via refining, electroplating, processing, mining, metallurgical activities, dyeing and other several metallic and metal based industrial and synthetic activities. Heavy metals like lead (Pb), mercury (Hg), cadmium (Cd), arsenic (As), Zinc (Zn), Cobalt (Co), Iron (Fe), and many other are considered as seriously noxious and toxic for the aquatic environment, human, and other aquatic lives and have damaging influences. Such heavy metals, which are very tough to be degraded, can be managed by reducing their potential through various processes like removal, precipitation, oxidation-reduction, bio-sorption, recovery, bioaccumulation, bio-mineralization etc. Microbes are known as talented bio-agents for the heavy metals detoxification process and fungi are one of the cherished bio-sources that show noteworthy aptitude of heavy metal sorption and metal tolerance. Thus, the main objective of the authors was to come with a comprehensive review having methodological insights on the novel and recent results in the field of mycoremediation of heavy metals. This review significantly assesses the potential talent of fungi in heavy metal detoxification and thus, in environmental restoration. Many reported works, methodologies and mechanistic sights have been evaluated to explore the fungal-assisted heavy metal remediation. Herein, a compact and effectual discussion on the recent mycoremediation studies of organic pollutants like dyes, petroleum, pesticides, insecticides, herbicides, and pharmaceutical wastes have also been presented.
Globefish-Inspired Balloon Catheter with Intelligent Microneedle Coating for Endovascular Drug Delivery

Balloon catheters exhibit important values in treating cardiovascular diseases, while their functions are still under improvements. Here, inspired by the thorn-hiding and deflating-inflating characteristics of globefish, intelligent balloon catheters decorated with invisible microneedles are presented for endovascular drug delivery to inhibit postintervention restenosis (PIRS). These microneedle balloon catheters (MNBCs) fabricated by dipping and rolling-assisted template replication contain three coating layers of sandwiched drug-carrying microneedles and black phosphorus (BP)-carrying gelatin. During the emplacement, the microneedles of MNBCs are hidden under the outermost gelatin protective layer, allowing smooth movements inside the blood vessel. After reaching the destination, the embedded BP converts near infrared (NIR) into heat, increases local temperature, and melts the gelatin layer, enabling the exposure and vascular penetration of the microneedles. Besides, as the innermost gelatin also melts, the microneedles can detach from the balloon catheter and be left inside the blood vessel for continuous drug release. Based on advantages of responsiveness, penetration capacity, and biosafety, it is demonstrated that the MNBCs behave satisfactorily in delivering rapamycin to inhibit abdominal aorta restenosis in rats. All these features indicate that these MNBCs are promising medical devices for clinical applications.
Hydrogen storage in clathrate hydrates: Current state of the art and future directions

Hydrogen is looked upon as the next generation clean energy carrier, search for an efficient material and method for storing hydrogen has been pursued relentlessly. Improving hydrogen storage capacity to meet DOE targets has been challenging and research efforts are continuously put forth to achieve the set targets and to make hydrogen storage a commercially realizable process. This review comprehensively summarizes the state of the art experimental work conducted on the storage of hydrogen as hydrogen clathrates both at the molecular level and macroscopic level. It identifies future directions and challenges for this exciting area of research. Hydrogen storage capacities of different clathrate structures - sI, sII, sH, sVI and semi clathrates have been compiled and presented. In addition, promising new approaches for increasing hydrogen storage capacity have been described. Future directions for achieving increased hydrogen storage and process scale up have been outlined. Despite few limitations in storing hydrogen in the form of clathrates, this domain receives prominent attention due to more environmental-friendly method of synthesis, easy recovery of molecular hydrogen with minimum energy requirement, and improved safety of the process. (C) 2014 Elsevier Ltd. All rights reserved.
Design, Synthesis, and Fungicidal Activity of Novel Plant Elicitors Based on a Diversity-Oriented Synthesis Strategy

The novel plant elicitors, 3-benzyl-5-[1-(2-oxo-4-phenyl-1-oxaspiro[4.5]dec-3-en-3-yl)ethylidene]-2-aminoimidazolin-4-one derivatives, were designed based on the diversity-oriented synthesis strategy and synthesized in four steps via the Knoevenagel condensation reaction as the key step. They were characterized by 1H NMR, 13C NMR, HR-ESI-MS, and X-ray diffraction. The position of the C═N bond of Z- and E-configuration compounds was determined by X-ray diffraction. The in vivo fungicidal activity evaluation revealed that most of these compounds exhibited remarkable activities (100%) against Pseudoperonospora cubensis at 400 μg/mL, among which compound 8e still exhibited excellent protective activity with a 50% inhibition rate at 0.1 μg/mL. Because the in vitro effect on tested phytopathogens was poor, the mechanism to induce the immune responses and reinforce the resistance of cucumber against Botrytis cinerea was studied. The results indicated that the compound 8e-mediated defense response against B. cinerea was based on the accumulation of pathogenesis-related proteins and cell wall reinforcement by callose deposition. Quantitative analysis of salicylic acid (SA) and jasmonic acid (JA) and the increased expression of induced resistance-related genes and the defense-associated phenylalanine ammonia lyase revealed that the immune response triggered by compound 8e was highly associated with the SA signaling pathway. Significant upregulation of JA-related genes Cs-AOS2 indicated that the JA signaling pathway was also influenced. It was also shown that the plants treated with compound 8e promoted primary root elongation, which resulted in enhanced plant growth. Most importantly, these compounds have completely new structures compared with the traditional plant elicitors. Further research of 8e-mediated plant disease resistance might have a great influence on the development of plant elicitors.
Boosting 3D Adversarial Attacks With Attacking on Frequency

Deep neural networks (DNNs) have been shown to be vulnerable to adversarial attacks in the image domain. Recently, 3D adversarial attacks, especially adversarial attacks on point clouds, have elicited mounting interest. However, adversarial point clouds obtained by previous methods show weak transferability and are easy to defend. To address these problems, in this paper we propose a strong point cloud attack method named AOF which pays more attention to the low-frequency component of point clouds. We combine the losses from point cloud and its low-frequency component to craft adversarial samples and focus on the low-frequency component of point cloud in the process of optimization. Extensive experiments validate that AOF can improve the transferability significantly compared to state-of-the-art (SOTA) attacks, and is more robust to state-of-the-art 3D defense methods. Otherwise, compared to adversarial point clouds generated by other adversarial attack methods, adversarial point clouds obtained by AOF contain more deformation than outlier. Code is available at: https://github.com/code-roamer/AOF.
Direct Intermode Selection for H.264 Video Coding Using Phase Correlation

The H.264 video coding standard exhibits higher performance compared to the other existing standards such as H. 263, MPEG-X. This improved performance is achieved mainly due to the multiple-mode motion estimation and compensation. Recent research tried to reduce the computational time using the predictive motion estimation, early zero motion vector detection, fast motion estimation, and fast mode decision, etc. These approaches reduce the computational time substantially, at the expense of degrading image quality and/or increase bitrates to a certain extent. In this paper, we use phase correlation to capture the motion information between the current and reference blocks and then devise an algorithm for direct motion estimation mode prediction, without excessive motion estimation. A bigger amount of computational time is reduced by the direct mode decision and exploitation of available motion vector information from phase correlation. The experimental results show that the proposed scheme outperforms the existing relevant fast algorithms, in terms of both operating efficiency and video coding quality. To be more specific, 82 similar to 92% of encoding time is saved compared to the exhaustive mode selection (against 58 similar to 74% in the relevant state-of-the-art), and this is achieved without jeopardizing image quality (in fact, there is some improvement over the exhaustive mode selection at mid to high bit rates) and for a wide range of videos and bitrates (another advantages over the relevant state-of-the-art).
Joint Superresolution and Rectification for Solar Cell Inspection

Visual inspection of solar modules is an important monitoring facility in photovoltaic power plants. Since a single measurement of fast CMOS sensors is limited in spatial resolution and often not sufficient to reliably detect small defects, we apply multiframe superresolution (MFSR) to a sequence of low-resolution measurements. In addition, the rectification and removal of lens distortion simplifies subsequent analysis. Therefore, we propose to fuse this preprocessing with standard MFSR algorithms. This is advantageous, because we omit a separate processing step, the motion estimation becomes more stable and the spacing of high-resolution pixels on the rectified module image becomes uniform w.r.t. the module plane, regardless of perspective distortion. We present a comprehensive user study showing that MFSR is beneficial for defect recognition by human experts and that the proposed method performs better than the state-of-the-art. Furthermore, we apply automated crack segmentation and show that the proposed method performs 3x better than bicubic upsampling and 2x better than the state-of-the-art for automated inspection.
MATEC: A lightweight neural network for online encrypted traffic classification

Increased awareness of privacy protection has led to a surge in the volume of encrypted traffic, which creates a heavy burden for efficient network management (e.g. quality-of-service guarantees). The opacity of encrypted traffic essentially requires high computational overheads to make traffic classification, which is even worse when encrypted traffic surges. However, existing deep learning approaches sacrifice the efficiency to obtain high-precision classification results, which are no longer suitable for scenarios with large volumes of encrypted traffic. In this paper, a lightweight and online approach implemented as MATEC is proposed. The way we optimize the classification process follows the "Maximizing the reuse of thin modules"design principle. The multi-head attention and the convolutional network are adopted in the thin module. Attributed to the one-step interaction of all packets and the parallel computing of the multi-head attention mechanism, a key advantage of our model is that the number of parameters and running time are significantly reduced. In addition, the effectiveness and efficiency of convolutional networks have been proved in traffic classification. Comparisons to the existing state-of-the-art models on three typical datasets demonstrate that the proposed MATEC model has higher accuracy and running efficiency. In addition, the number of parameters is reduced to 1.8% of the state-of-the-art models and the training time halves.
Desertification assessment in China: An overview

Desertification, land degradation in arid, semi-arid, and dry sub-humid regions, is a global environmental problem. Accurate assessment of the status, change, and trend of desertification will be instrumental in developing global actions to prevent and eradicate the problem. As one of the most seriously affected countries, China has made great efforts to combat desertification. Although improvements have been made in some areas, degradation continues to expand and intensify throughout the entire country. Further land degradation assessments, such as assessments made by the Chinese Committee for Implementing UN Convention to Combat Desertification (CCICCD), will be necessary to ensure successful decision-making, to combat increasing desertification, and to implement Western strategies. This paper overviews the state-of-the-art desertification assessments on both the national and local levels. Also, two major problems facing the assessment of degradation-the uncertainty of baseline assessments and indictor systems and the misuse of remotely sensed data sources-are presented along with suggestions for possible solutions to these problems. (c) 2005 Published by Elsevier Ltd.