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The effect of colloidal nanoparticles on the phase changes of the amphiphilic AB linear diblock, A1A2B, and A2B heteroarm star copolymers confined between two polymer brush substrates was investigated by using a real-space self-consistent field theory. By changing the concentrations of nanoparticles and polymer brushes, the phase structure of the amphiphilic AB copolymer transforms from lamellar to core-shell hexagonal phase to cylinder phase. The pattern of A2B heteroarm star copolymer changes from core-shell hexagonal phases to lamellar phases and the layer decreases when increasing the density of the polymer brushes. The results showed that the phase behavior of the system is strongly influenced by the polymer brush architecture and the colloidal nanoparticle numbers. The colloidal nanoparticles and the soft confined surface of polymer brushes make amphiphilic AB copolymers easier to form ordered structures. The dispersion of the nanoparticles was also investigated in detail. The soft surfaces of polymer brushes and the conformation of the block copolymers work together to force the nanoparticles to disperse evenly. It will give helpful guidance for making some new functional materials by nano etching technology, nano photoresist, and nanoprinting. [ABSTRACT FROM AUTHOR]

Existing Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods are mostly suitable for simple systems with fewer factors, and lack effective integration of expert knowledge and experience from large-scale group populations, resulting in a potential compromise of the quality of the initial direct relation (IDR) matrix. To make DEMATEL better suited for the identification of critical factors in complex systems, this paper proposes a hierarchical DEMATEL method for large-scale group decision-making. Considering the limitations of expert knowledge and experience, a method based on expert consistency network for constructing the expert weight matrix is designed. The expert consistency network is constructed for different elements, and the weights of experts in different elements are determined using the clustering coefficient. Following the principles of the classic DEMATEL method, the steps for identifying key elements in complex systems using the large-scale group-hierarchical DEMATEL method are summarized. To objectively test the effectiveness and superiority of the decision algorithm, the robustness of the algorithm is analyzed in an interference environment. Finally, the superiority of the proposed method and algorithm is verified through a case study, which demonstrating that the proposed decision-making method is suitable for group decision-making in complex systems, with high algorithm stability and low algorithm deviation. [ABSTRACT FROM AUTHOR]

Acoustic wave scattering and fluid perturbations produced by interactions between incident acoustic wave and confined orifice flow were investigated by a combined numerical solution containing nonlinear flow simulation and linearized acoustic simulation. In flow simulations, the mainstream Reynolds number was fixed at 10,000, which relates to the cooling pipe system of lithography. Turbulent flow fields corresponding to different orifice geometries were solved by an opensource finite volume solver OpenFOAM with Reynolds-averaged Navier–Stokes turbulence model. The turbulence database could efficiently improve the accuracy of subsequent linearized acoustic simulations as the viscosity dissipations were considered. In acoustic simulations, the linearized Navier-Stokes equations were solved by a finite element solver with transformation into frequency domain. The incident acoustic waves with varying frequencies from 500 Hz to 4000 Hz were arranged first at the inlet and then the outlet surfaces, enabling a two-port analysis on the transmission and reflection coefficients of acoustic waves. The numerical setup and the two-port model were well validated by results in literature. Generally, acoustic waves tend to gradually dissipate as their frequencies increase or the opening ratio of the ducted orifice decreases. However, the nonlinear variation in the transmission and reflection coefficients against the frequency variation of the incident acoustic waves could be investigated by increasing the thickness ratio. The acoustically induced fluid perturbations that were characterized by the Q-criterion could form a ring shape vortex structure in the vicinity of the orifice edge and then develop into disk-like packets. When the circumferential shape of the orifice was changed to a square, the attenuation of the incident acoustic waves corresponded to the intensity of the three-dimensionality of the acoustic-induced vortex structures, which indicated a greater energy transfer from the acoustic waves to the fluid perturbations. [ABSTRACT FROM AUTHOR]

The core issue of learning-to-rank (LTR) for document retrieval lies in finding an optimal ranking policy to meet the search intent of the user. The majority of proposed LTR approaches treat the ranking as a static process, employing a fixed ranking policy to immediately assign scores to documents. By contrast, ranking is not a static but an interactive process where the user continues interacting with the document retrieval system through information exchange such as search intent (e.g., rating or clicking for the retrieved items). We model the interactive ranking process (IRP), and propose an Attention-Based Interactive LTR model (AIRank) to constitute an intent-aware flexible ranking policy to gratify the user’s need. To enhance the ranking quality, the inherent relations among documents are procured by the self-attention method to contribute to an enriched user intent representation. Furthermore, we mend the policy gradient learning method to train the AIRank in the IRP. Experiments demonstrate the effectiveness of AIRank compared to the state-of-the-art methods in terms of normalized discounted cumulative gain and expected reciprocal rank. [ABSTRACT FROM AUTHOR]

Leveraging global state information to enhance policy optimization is a common approach in multi-agent reinforcement learning (MARL). Even with the supplement of state information, the agents still suffer from insufficient exploration in the training stage. Moreover, training with batch-sampled examples from the replay buffer will induce the policy overfitting problem, i.e., multi-agent proximal policy optimization (MAPPO) may not perform as good as independent PPO (IPPO) even with additional information in the centralized critic. In this paper, we propose a novel noise-injection method to regularize the policies of agents and mitigate the overfitting issue. We analyze the cause of policy overfitting in actor–critic MARL, and design two specific patterns of noise injection applied to the advantage function with random Gaussian noise to stabilize the training and enhance the performance. The experimental results on the Matrix Game and StarCraft II show the higher training efficiency and superior performance of our method, and the ablation studies indicate our method will keep higher entropy of agents' policies during training, which leads to more exploration. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel deep architecture by combining multiple sensors for 3D object detection, named MSL3D. While recently LiDAR-Camera methods introduce additional semantic cues, working with fewer false detections, there is still a performance gap compared LiDAR-only methods. We argue that this gap is caused for two reasons: 1) the 3D spherical receptive fields of the set abstraction of the point clouds are not aligned with the 2D pixel-level receptive fields of the image. 2) the premature introduction of image information makes it is difficult to apply data augmentation both LiDAR and image synchronously. For the first problem, we extend 3D set abstraction to a 2D set abstraction that can transform the 2D image features to the 3D sphere to unify the receptive field of multi-modal data. For the second problem, we design a novel two-stage 3D detection framework that employs the LiDAR-only backbone in the first stage to estimate high-recall and high-quality proposals and then integrates the image and point clouds information for box refinement and confidence prediction. Besides, we add two auxiliary networks to effectively learn image features and point cloud features when using different multi-modal data augmentation strategies synchronously. Moreover, we design a consistency-structure generator using stereo images to determine whether any of a point in the 3D space belongs to the contour of the object, thereby supplementing the sparse point cloud information. Extensive experiments on the popular KITTI 3D objects detection dataset show that our proposed MSL3D achieves better performance comparing with other LiDAR-Only or LiDAR-Camera fusion approaches. [ABSTRACT FROM AUTHOR]

Xanthatin (XT) is a sesquiterpene lactone isolated from the Chinese herb Xanthium, which belongs to the Asteraceae family. In this study, we developed an inflammation model via stimulating macrophage cell line (RAW 264.7 cells) with lipopolysaccharide (LPS), which was applied to assess the anti-inflammatory effect and probable mechanisms of xanthatin. When compared with the only LPS-induced group, cells that were pretreated with xanthatin were found to decrease the amount of nitric oxide (NO), reactive oxygen species (ROS) and associated pro-inflammatory factors (TNF-α, IL-1β and IL-6), and downregulate the mRNA expression of iNOS, COX-2, TNF-α, IL-1β, and IL-6. Interestingly, phosphorylated levels of related proteins (STAT3, ERK1/2, SAPK/JNK, IκBα, p65) were notably increased only with the LPS-activated cells, while the expression of these could be reverted by pre-treatment with xanthatin in a dose-dependent way. Meanwhile, xanthatin was also found to block NF-κB p65 from translocating into the nucleus and activating inflammatory gene transcription. Collectively, these results demonstrated that xanthatin suppresses the inflammatory effects through downregulating the nuclear factor kappa-B (NF-κB), mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription (STATs) signaling pathways. Taken together, xanthatin possesses the potential to act as a good anti-inflammatory medication candidate. [ABSTRACT FROM AUTHOR]

Excessive inflammation leads to periodontitis, which inhibits the osteogenic differentiation of human dental pulp stem cells (hDPSCs), irreversibly injured and difficultly repaired for the important dental pulp. Hence, it is necessary to study the functional gene to enhance the osteogenic differentiation of hDPSCs. Previous found that SNHG7 expression was increased in the osteogenic differentiation of hDPSCs. However, the regulatory functions of SNHG7 on osteogenic differentiation of hDPSCs in the inflammatory microenvironment still remains unknown. In this study, hDPSCs treatment with 50 ng/mL TNF-α to mimic the inflammatory microenvironment, then cultured in osteoblast differentiation medium for 14 days. SNHG7, miR-6512–3p, BSP, DSPP, DMP-1, RUNX2 and OPN in hDPSCs were detect by RT-qPCR. We found that SNHG7 expression was reduced during the osteogenic differentiation of hDPSCs after different concentrations TNF-α treatment. SNHG7 overexpression improved the TNF-α-induced suppression of calcium deposition, ALP activity, and the expression of BSP, DSPP, DMP-1, RUNX2 and OPN. Furthermore, SNHG7 can sponge with miR-6512–3p. miR-6512–3p expression was increased during the osteogenic differentiation of hDPSCs after different concentrations TNF-α treatment while inhibited after SNHG7 overexpression. knockdown of miR-6512–3p improved the TNF-α-induced suppression of calcium deposition, ALP activity, and the expression of BSP, DSPP, DMP-1, RUNX2 and OPN. Finally, miR-6512–3p overexpression reversed the effect of SNHG7 on the osteo/dentinogenic differentiation of TNF-α-treated hDPSCs. In conclusions, SNHG7 improves the osteogenic differentiation of hDPSCs by inhibiting miR-6512–3p expression under 50 ng/mL TNF-α-induced inflammatory environment, which provided potential targets for the treatment of periodontitis. • ng/mL TNF-α treatment inhibited the hDPSCs osteo/dentinogenic differentiation. • SNHG7 expression was reduced in hDPSCs after 50 ng/mL TNF-α treatment. • SNHG7 improved the osteo/dentinogenic differentiation of TNF-α-induced hDPSCs. • SNHG7 inhibited miR-6512–3p expression in TNF-α-induced hDPSCs. [ABSTRACT FROM AUTHOR]

The currently predominant token-to-token attention mechanism has demonstrated its ability to capture word dependencies in neural machine translation. This mechanism treats a sequence as bag-of-words tokens and compute the similarity between tokens without considering their intrinsic interactions. In this paper, we argue that this attention mechanism may miss opportunity of take advantage of the state information through multiple time steps. Thus, we propose a Gated State Network which manipulates the state information flow with sequential characteristics. We also incorporate a Focal Adaptive Attention Network which utilizes a Gaussian distribution to concentrate the attention distribution to a predicted focal position and its neighborhood. Experimental results on WMT'14 English–German and WMT'17 Chinese–English translation tasks demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Background: Secreted frizzled-related protein 2 (SFRP2) in circulating tumor DNA (ctDNA) is related to gastric cancer (GC) proliferation. However, whether methylated SFRP2 in ctDNA serves as the biomarker in GC patients remains unknown. Aims: To investigate the relationship between methylated SFRP2 and the clinical outcomes of GC patients. Methods: One hundred and forty-eight GC patients receiving systemic chemotherapy were collected during 2015–2017. Aberrant SFRP2 methylation was detected before and after chemotherapy by digital PCR-based technologies. Results: Baseline SFRP2 methylation positively correlated with lymph node status (P < 0.001), distant metastasis (P < 0.001) and TNM stage (P = 0.005). The top 50% methylated SFRP2 had shorter progression-free survival (PFS) and overall survival (OS) than those with bottom 50% in stage III GC patients (median PFS, 11.0 vs. NR months; HR 13.05; 95% CI 3.05–55.95; median OS 17.0 vs. NR months; HR 7.80; 95% CI 1.81–33.60) and stage IV GC patients (median PFS, 4.0 vs. 7.0 months; HR 2.74; 95% CI 1.58–4.78; median OS 12.0 vs. 16.0 months; HR 3.14; 95% CI 1.67–5.92). Besides, the increased methylated SFPR2 from baseline to post-treatment was related to the worse PFS and OS among stage IV patients (median PFS, 5.0 vs. 7.0 months; HR 2.17; 95% CI 1.25–3.76; median OS 12.0 vs. 15.5 months; HR 3.51; 95% CI 1.94–6.35), but not to stage III patients. Conclusions: SFRP2 methylation and dynamic change are associated with GC prognosis. Our findings provide potential biomarker detection approach in ctDNA for prognosis prediction and dynamic monitoring among GC patients. [ABSTRACT FROM AUTHOR]

Discovering drug–target (protein) interactions (DTIs) is of great significance for researching and developing novel drugs, having a tremendous advantage to pharmaceutical industries and patients. However, the prediction of DTIs using wet-lab experimental methods is generally expensive and time-consuming. Therefore, different machine learning-based methods have been developed for this purpose, but there are still substantial unknown interactions needed to discover. Furthermore, data imbalance and feature dimensionality problems are a critical challenge in drug-target datasets, which can decrease the classifier performances that have not been significantly addressed yet. This paper proposed a novel drug–target interaction prediction method called PreDTIs. First, the feature vectors of the protein sequence are extracted by the pseudo-position-specific scoring matrix (PsePSSM), dipeptide composition (DC) and pseudo amino acid composition (PseAAC); and the drug is encoded with MACCS substructure fingerings. Besides, we propose a FastUS algorithm to handle the class imbalance problem and also develop a MoIFS algorithm to remove the irrelevant and redundant features for getting the best optimal features. Finally, balanced and optimal features are provided to the LightGBM Classifier to identify DTIs, and the 5-fold CV validation test method was applied to evaluate the prediction ability of the proposed method. Prediction results indicate that the proposed model PreDTIs is significantly superior to other existing methods in predicting DTIs, and our model could be used to discover new drugs for unknown disorders or infections, such as for the coronavirus disease 2019 using existing drugs compounds and severe acute respiratory syndrome coronavirus 2 protein sequences. [ABSTRACT FROM AUTHOR]

In the realm of flexible optoelectronic devices, intrinsic flexible fully π‐conjugated polymers (FπCPs) assume a pivotal role owing to their concurrent intrinsic viscoelasticity and robust optoelectronic properties. As flexible devices are destined to encounter diverse stress environments, the selection of functional materials based on mechanical requirements becomes imperative. Here, VPERD assessment system is introduced to scrutinize the mechanical properties of side‐chain plasticizing FπCPs. The acronym VPERD encapsulates five key aspects of mechanical characteristics, namely viscidity (V), plasticity (P), elasticity (E), rigidity (R), and ductility (D). The mechanical characteristics of FπCPs are tuned through the control of flexible chain density (FCD). Enhancing FCD induces superior chain softness, favorable solubility, and heightened viscoplasticity. Through precise regulation of FCD and thoughtful structural design, freestanding FπCPs nano‐films exhibit a remarkable maximum fracture strain of ≈50%. Deep‐blue flexible polymer light‐emitting diodes (PLEDs) reveal that maintaining FCD at ≈50% achieves a balance between mechanical and optoelectronic properties. The stretched films after strain fatigue both show that mild strain is conducive to enhancing the efficiency of FπCPs films and devices. According to VPERD assessment system, the prerequisite for achieving intrinsically flexible FπCPs lies in controlling the degree of side‐chain internal plasticization through the tuning of FCD. [ABSTRACT FROM AUTHOR]

A target-triggered strand displacement-assisted target recycling based on carbon dots-based fluorescent probe and mesoporous silica nanoparticles@polydopamine (MSNs@PDA) was established to detect miRNA. The surface of MSNs rich in mesopores was coated with a layer of PDA, which can adsorb and quench the fluorescence of single-stranded Fuel DNA with fluorescent carbon dots (CDs) modified at the end through fluorescence resonance energy transfer (FRET). After adding double-stranded DNA-gold nanoparticles (dsDNA-AuNPs) and target let-7a, it will trigger two toehold-mediated strand displacement reactions (TSDR), leading to the recovery of fluorescence and the recycling of target let-7a (excitation wavelength: 380 nm; emission wavelength: 458 nm). The recovery value of fluorescence is proportional to the logarithm of the target microRNA let-7a concentration, thus realizing the sensitivity amplification detection of disease markers. The MSNs@PDA@Fuel DNA-CDs/dsDNA-AuNPs nanoplatform based on the strategy of "on–off–on" and TSDR cyclic amplification may hold great potential as an effective and safe nanoprobe for accurate fluorescence imaging of diseases related to miRNA with low abundances. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a serious and heterogeneous psychiatric disorder that needs accurate diagnosis. Resting-state functional MRI (rsfMRI), which captures multiple perspectives on brain structure, function, and connectivity, is increasingly applied in the diagnosis and pathological research of MDD. Different machine learning algorithms are then developed to exploit the rich information in rsfMRI and discriminate MDD patients from normal controls. Despite recent advances reported, the MDD discrimination accuracy has room for further improvement. The generalizability and interpretability of the discrimination method are not sufficiently addressed either. Here, we propose a machine learning method (MFMC) for MDD discrimination by concatenating multiple features and stacking multiple classifiers. MFMC is tested on the REST-meta-MDD data set that contains 2428 subjects collected from 25 different sites. MFMC yields 96.9% MDD discrimination accuracy, demonstrating a significant improvement over existing methods. In addition, the generalizability of MFMC is validated by the good performance when the training and testing subjects are from independent sites. The use of XGBoost as the meta classifier allows us to probe the decision process of MFMC. We identify 13 feature values related to 9 brain regions including the posterior cingulate gyrus, superior frontal gyrus orbital part, and angular gyrus, which contribute most to the classification and also demonstrate significant differences at the group level. The use of these 13 feature values alone can reach 87% of MFMC's full performance when taking all feature values. These features may serve as clinically useful diagnostic and prognostic biomarkers for MDD in the future. • A new MDD discrimination method MFMC is proposed. • MFMC is tested on REST-meta-MDD including over 2400 subjects. • MFMC outperforms existing methods with significant improvements. • The good generalizability of MFMC is verified. • MFMC identifies 13 features related with 9 brain regions important for MDD. [ABSTRACT FROM AUTHOR]

Originating from model-free reinforcement learning (RL), many modern multi-agent reinforcement learning (MARL) algorithms are usually armed with the paradigm of Centralized Training with Decentralized Execution (CTDE) to mitigate the non-stationary problem and make the training process stable. However, these methods still suffer from sample inefficiency and slow training convergence as in the single-agent reinforcement learning setting. Many common methods aiming to tackle these problems utilize the experience buffer and parallel training mechanism to speed up the training process, which would cost more computing resources and may still underuse the sampled experiences. In this paper, we propose R egularization - A dapted A nderson A cceleration (RA3) for model-free, off-policy MARL algorithms. Under the CTDE paradigm, this specific RA3 approach treats the joint action-value function update as a fixed-point iteration task and speeds up the training process with the same amount of sampled experiences as in the baseline algorithms. Furthermore, our RA3 employs an adaptive regularization strategy related to Bellman residuals to stabilize the update process and enhance the training performance. Experimental results demonstrate that the improved learning speed and superior performance of our proposed method are significantly improved on the predator–prey game and the challenging StarCraft II micromanagement benchmark tasks. [ABSTRACT FROM AUTHOR]

Graph clustering has received significant attention in recent years due to the breakthrough of graph neural networks (GNNs). However, GNNs frequently assume strong data homophily, which is not true in many real-world applications. Furthermore, practical graphs are typically noisy and sparse, which inevitably degrades the clustering performance. To this end, we propose a novel Contrastive Graph Clustering (CGC) method with adaptive filter framework. We first design an adaptive filter that can automatically learn a suitable filter for different data, mining holistic information beyond low-frequency components and encoding topology structure information into features. Afterward, we learn a refined graph based on a graph-level contrastive mechanism, which further boosts graph discriminability. Extensive experiments show that the proposed CGC method achieves significant improvement over state-of-the-art methods on several benchmark datasets. In particular, our simple method, which does not employ neural networks, outperforms many deep learning approaches. • High-frequency information is considered for graph clustering. • Contrastive regularizer is applied to refine graph structure. • Homophilic and heterophilic graphs are evaluated. [ABSTRACT FROM AUTHOR]

Graph neural networks (GNNs) have drawn increasing attention in recent years and achieved remarkable performance in many graph-based tasks, especially in semi-supervised learning on graphs. However, most existing GNNs are based on the message-passing paradigm to iteratively aggregate neighborhood information in a single topology space. Despite their success, the expressive power of GNNs is limited by some drawbacks, such as inflexibility of message source expansion, negligence of node-level message output discrepancy, and restriction of single message space. To address these drawbacks, we present a novel message-passing paradigm, based on the properties of multi-step message source, node-specific message output, and multi-space message interaction. To verify its validity, we instantiate the new message-passing paradigm as a Dual-Perception Graph Neural Network (DPGNN), which applies a node-to-step attention mechanism to aggregate node-specific multi-step neighborhood information adaptively. Our proposed DPGNN can capture the structural neighborhood information and the feature-related information simultaneously for graph representation learning. Experimental results on six benchmark datasets with different topological structures demonstrate that our method outperforms the latest state-of-the-art models, which proves the superiority and versatility of our method. To our knowledge, we are the first to consider node-specific message passing in the GNNs. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the intra-examination agreement between multi-echo gradient echo (MEGE) and confounder-corrected chemical shift-encoded (CSE) sequences for liver T2*/R2* estimations in a wide range of T2*/R2* and proton density fat fraction (PDFF) values. Exploratorily, to search for the T2*/R2* value where the agreement line breaks and examine differences between regions of low and high agreement. Methods: Consecutive patients at risk for liver iron overload who underwent MEGE and CSE sequences within the same exam at 1.5 T were retrospectively selected. Regions of interest were drawn in the right and one in the left liver lobes on post-processed images for R2*(sec−1) and PDFF (%) estimation. Agreement between MEGE-R2* and CSE-R2* was evaluated using intra-class correlation coefficient (ICC) and Bland–Altman analysis. 95% confidence intervals (CI) were computed. Segment-and-regression analysis was performed to find the point where the agreement between sequences is interrupted. Regions of low and high agreement were examined using tree-based partitioning analyses. Results: 49 patients were included. Mean MEGE-R2* was 94.2 s−1 (range: 31.0–737.1) and mean CSE-R2* 87.7 (29.7–748.1). Mean CSE-PDFF was 9.12% (0.1–43.3). Agreement was strong for R2* estimations (ICC: 0.992,95%CI 0.987,0.996), but the relation was nonlinear and possibly heteroskedastic. Lower agreement occurred when MEGE-R2* > 235 s−1, with MEGE-R2* values consistently lower than CSE-R2*. Higher agreement was observed when PDFF < 14%. Conclusion: MEGE-R2* and CSE-R2* strongly agree, though at higher iron content, MEGE-R2* is consistently lower than CSE-R2*. In this preliminary dataset, a breaking point for agreement was found at R2* > 235. Lower agreement was observed in patients with moderate to severe liver steatosis. [ABSTRACT FROM AUTHOR]

MALAT1 has been implicated in tumor progression. But the mechanism and role underlying MALAT1 in non-small cell lung cancer (NSCLC) cell resistance to gemcitabine (GEM) remain rarely understood. Through bioinformatics analysis, we predicted MALAT1/miR-27a-5p/PBOV1 regulatory axis and constructed GEM resistant A549/GEM cell line, and A549 was the parent cell line. qRT-PCR was utilized to assess MALAT1, miR-27a-5p and PBOV1 expression in A549 and A549/GEM cells. MTT method and colony formation assay were utilized to measure cell viability and cell proliferation. Flow cytometry was conducted to assess cell cycle and cell apoptosis. Wound healing and Transwell assays were conducted to measure cell migratory and invasive potentials. Dual-luciferase reporter gene assay and RNA immunoprecipitation were utilized to identify the targeted relationship between MALAT1 and miR-27a-5p, and the former assay was also utilized to determine the targeted relationship between miR-27a-5p and PBOV1. The impacts of MALAT1/miR-27a-5p/PBOV1 on tumor growth and GEM resistance of NSCLC cells in vivo were validated by using the tumor xenograft model. MALAT1 was observed to be highly expressed in tissues and cells of GEM resistant patients. Forced level of MALAT1 could markedly enhance A549 cell resistance to GEM, but this impact could be weakened by silencing MALAT1. MALAT1 downregulated miR-27a-5p level. PBOV1 was the target of miR-27a-5p and could significantly enhance GEM resistance of NSCLC cell. MALAT1 facilitated tumor growth in vivo via targeting miR-27a-5p/PBOV1 and enhanced resistance of NSCLC cells to GEM. MALAT1/miR-27a-5p/PBOV1 axis was implicated in NSCLC cell resistance to GEM. We deepened our understanding about how MALAT1 enhanced NSCLC cell resistance to GEM and provided development of therapeutic strategy for NSCLC with a possible target. • LncRNA MALAT1 was associated with gemcitabine resistance in NSCLC cells. • LncRNA MALAT1 targeted miR-27a-5p in NSCLC. • PBOV1 was the direct target of miR-27a-5p in NSCLC. • LncRNA MALAT1 enhanced non-small cell lung cancer cell resistance to gemcitabine by directly affecting miR-27a-5p/PBOV1 axis. [ABSTRACT FROM AUTHOR]

• Silencing TRIM66 hindered cell malignant phenotype of non-small cell lung cancer; • TRIM66 interacted with MMP9 in non-small cell lung cancer; • MMP9 activated TGF-β/SMAD pathway; • TRIM66/MMP9/TGF-β/SMAD axis promoted non-small cell lung cancer progression. To investigate regulatory function and underlying mechanism of TRIM66 in non-small cell lung cancer (NSCLC). TRIM66 and MMP9 expression in NSCLC cells and tissues was assayed via qRT-PCR and western blot. CCK-8, colony formation, Transwell and flow cytometry assays were conducted to measure cell functional alternations in NSCLC. Western blot was employed to measure expression as well as phosphorylation levels of epithelial-mesenchymal transition-(EMT) and TGF-β/SMAD pathways-related proteins. Co-immunoprecipitation (Co-IP) assay was done to probe interaction between TRIM66 and MMP9. Xenograft in vivo experiment and tumor metastasis model in nude mice were utilized to investigate effects of TRIM66 on tumor growth of NSCLC. TRIM66 and MMP9 were conspicuously highly expressed in NSCLC cells and tissues. High TRIM66 level was markedly correlated with metastasis. Silencing TRIM66 prominently repressed the proliferation, migration and invasion of transfected cells, while inducing cell apoptosis. Whereas forced expression of TRIM66 exerted the opposite effect. The aberrant expression of TRIM66 modulated EMT pathway. TRIM66 also regulated MMP9 expression, and the interaction between them was validated by Co-IP assay. Overexpression of MMP9 could activate TGF-β/SMAD pathway. Rescue experiments manifested that si-MMP9 or SB431542 could partially reverse phenotypes induced by TRIM66. In vivo experiments revealed that silencing TRIM66 could hamper NSCLC tumor growth and metastasis. TRIM66 and MMP9 were up-regulated in NSCLC. TRIM66 facilitated the malignant progression of NSCLC through modulating MMP9-mediated TGF-β/SMAD pathway. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC).Methods: For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves.Results: A Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718-0.735) and 0.721 (95% CI, 0.709-0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691-0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system.Conclusion: We developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions. [ABSTRACT FROM AUTHOR]

Conjugated polymers with p‐orbital overlap show intramolecular‐conformation‐dependent photophysical and electrical properties. Compared to the non‐planar segments, the planar conformation segments have a relatively long effective conjugated length and rigid backbone structure, which are beneficial for the enhancement of optoelectronic properties. Herein, the effect of film thickness on the formation capacity of planar (β) conformations in polyfluorene (poly[4‐(octyloxy)‐9,9‐diphenylfluorene‐2,7‐diyl]‐co‐[5‐(octyloxy)‐9,9‐diphenylfluorene‐2,7‐diyl], PODPF) for the fabrication of stable deep‐blue polymer light‐emitting diodes (PLEDs) is explored. Thickness‐tunable films with thicknesses ranging from 15 to 270 nm by controlling the concentration of precursor solution are prepared. The main observations are as follows. The PODPF chains in thin films are less likely to adopt the β conformations associated with the loose interchain packing in nano‐aggregates than those in thick films. Red‐shifted and well‐resolved emission spectra are observed for the annealed film with a high thickness, indicating the greater presence of β‐conformation segments. More interestingly, interchain aggregation is a necessary but not sufficient condition for the formation of β conformations. Finally, PLEDs based on β‐conformation segments have outstanding brightness, low turn‐on voltage, and stable deep‐blue electroluminescent behavior, confirming the unique advantage of planar conformation for optoelectronic applications. [ABSTRACT FROM AUTHOR]

To evaluate the value of nanopore targeted sequencing in diagnosing pneumonia pathogens. This large-scale multicentre prospective study performed in 8 hospitals across China from April to October 2022. Hospitalised patients with a diagnosis of pneumonia at admission were included. Complete clinical data were collected, and bronchoalveolar lavage fluid were obtained from each patient. These samples underwent simultaneous testing using conventional microbial testing, metagenomic next-generation sequencing, and nanopore targeted sequencing. A total of 218 patients were included. Among the 168 cases of pulmonary infection, 246 strains of pathogens were confirmed. Nanopore targeted sequencing outperformed conventional microbial testing, identifying more pathogens with a sensitivity increase of 47.9% (77.2% vs. 29.3%). Metagenomic next-generation sequencing had a sensitivity of 82.9%. Total of 70.1% patients had consistent results in both metagenomic next-generation sequencing and nanopore targeted sequencing. Nanopore targeted sequencing exhibited significantly higher sensitivity in detecting Pneumocystis jiroveci, cytomegalovirus, Mycobacterium tuberculosis, Nontuberculous mycobacteria, Streptococcus pneumoniae, and Mycoplasma pneumoniae compared to conventional microbial testing. However, metagenomic next-generation sequencing demonstrated higher sensitivity than nanopore targeted sequencing for Aspergillus (88.5% vs. 53.8%). Regarding the detection of co-infections, nanopore targeted sequencing displayed significantly higher sensitivity than conventional microbial testing (76.7% vs. 28.7%) and was on par with metagenomic next-generation sequencing (76.7% vs. 82.9%). Nanopore targeted sequencing performs equally well as metagenomic next-generation sequencing in bronchoalveolar lavage fluid for pathogen diagnosis in pneumonia, both methods showing higher sensitivity than conventional microbial testing. Nanopore targeted sequencing can be considered a reliable method for diagnosing pathogens in pneumonia. [ABSTRACT FROM AUTHOR]

[8][9][10][11] Organophosphorus compounds containing epoxy groups are generally prepared by the reaction of unstable and toxic phosphorus halides with alcohols containing an epoxide group (Scheme 1a). Solvent-free reaction, alkylation, epichlorohydrocarbons, phosphonic acids, tandem reaction, epoxy phosphinates Keywords: solvent-free reaction; alkylation; epichlorohydrocarbons; phosphonic acids; tandem reaction; epoxy phosphinates EN solvent-free reaction alkylation epichlorohydrocarbons phosphonic acids tandem reaction epoxy phosphinates 1715 1718 4 08/18/23 20230901 NES 230901 Graph Owing to its high reactivity, the epoxy group is important in syntheses of pharmaceuticals and bioactive natural products. [Extracted from the article]

Green‐processable printed large‐area light‐emitting diode (LED) is the crucial component of the high quality solid lighting and flat‐panel display. Accelerating the replacement from fossil‐based solvents to sustainable ecofriendly solvent is desirable for solution‐based printed organic electronics. Herein, by simple introducing methyl to the benzene groups of polydiarylfluorene‐based polymer, this work realizes the solution processing of blue polymer light‐emitting diodes (PLEDs) with a bio‐based solvent of limonene toward large‐area printed display. Film processed from this solvent exhibits satisfactory morphology and remarkable photophysical performances, even though the polymer chains show more serious aggregation in solution. What's more, devices fabricated with spin‐coated films present higher external quantum efficiency (EQE) and better spectra repeatability. Encouraged by the good film‐forming ability of this polymer in limonene, this work realizes the fabrication of printed large‐area films (5 × 5 cm2) with uniform emission and surface morphology by blade coating. Furthermore, this work develops passive matrix (PM) PLEDs arrays with 20 × 20 pixels that can dynamically display monochrome letters and numbers, demonstrating the potential application of cost‐effective printing techniques in large‐area display. [ABSTRACT FROM AUTHOR]

Background: Peach (Prunus persica L. Batsch) is one of the most popular fruits worldwide. Although the reference genome of 'Lovell' peach has been released, the diversity of genome-level variations cannot be explored with one genome. To detect these variations, it is necessary to assemble more genomes. Results: We sequenced and de novo assembled the genome of 'Feichenghongli' (FCHL), a representative landrace with strict self-pollination, which maintained the homozygosity of the genome as much as possible. The chromosome-level genome of FCHL was 239.06 Mb in size with a contig N50 of 26.93 Mb and only 4 gaps at the scaffold level. The alignment of the FCHL genome with the reference 'Lovell' genome enabled the identification of 432535 SNPs, 101244 insertions and deletions, and 7299 structural variants. Gene family analysis showed that the expanded genes in FCHL were enriched in sesquiterpenoids and triterpenoid biosynthesis. RNA-seq analyses were carried out to investigate the two distinct traits of late florescence and narrow leaves. Two key genes, PpDAM4 and PpAGL31, were identified candidates for the control of flower bud dormancy, and an F-box gene, PpFBX92, was identified as a good candidate gene in the regulation of leaf size. Conclusions: The assembled high-quality genome could deepen our understanding of variations among diverse genomes and provide valuable information for identifying functional genes and improving the molecular breeding process. [ABSTRACT FROM AUTHOR]

Large‐area polymer light‐emitting diodes (PLEDs) manufactured by printing are required for flat‐panel lighting and displays. Nevertheless, it remains challenging to fabricate large‐area and stable deep‐blue PLEDs with narrowband emission due to the difficulties in precisely tuning film uniformity and obtaining single‐exciton emission. Herein, efficient and stable large‐area deep‐blue PLEDs with narrowband emission are prepared from encapsulated polydiarylfluorene. Encapsulated polydiarylfluorenes presented an efficient and stable deep‐blue emission (peak: 439 nm; full width at half maximum (FWHM): 39 nm) in the solid state due to their single‐chain emission behavior without inter‐backbone chain aggregation. Large‐area uniform blade‐coated films (16 cm2) are also fabricated with excellent smoothness and morphology. Benefitting from efficient emission and excellent printed capacity, the blade‐coated PLEDs with a device area of 9 mm2 realized uniform deep‐blue emission (FWHM: 38 nm; CIE: 0.153, 0.067), with a corresponding maximum external quantum efficiency and the brightness comparable to those of devices based on spin‐coated films. Finally, considering the essential role of deep‐blue LEDs, a preliminary patterned PLED array with a pixel size of 800 × 1000 µm2 and a monochrome display is fabricated, highlighting potential full‐color display applications. [ABSTRACT FROM AUTHOR]

Spin-torque oscillators (STOs) are unique spintronic devices in which spin current induces the precession of magnetization in the oscillation layer. In this study, we demonstrate coupled out-of-plane oscillation between two oscillation layers within an STO. The coupled oscillation state is observed in the magnetoresistance spectra as well as its degradation due to the mixing of the free oscillation state depending on the bias current. These behaviors are analytically described and numerically reproduced based on the Landau–Lifshitz–Gilbert equation. Since the STO is fabricated in the write head of a hard disk drive, the coupled oscillation state and the subsequent microwave magnetic field are applicable for microwave-assisted magnetic recording for high-density recording. [ABSTRACT FROM AUTHOR]

Control of the secondary conformational behavior of light‐emitting conjugated polymers (LCPs) is essential to obtain deep‐blue emission with a narrowband and stable color purity. Naturally π–π interactions induced by the planar aromatic segments may be easily observed in liner‐type LCPs, which lead to reduced emission efficiency, color purity, and energy bandgap. Herein, an alternating copolymerization strategy is proposed to obtain the singlet exciton behavior of a planar conformational segment from polydiarylfluorenes‐copolymers (P7‐6DPF, P7‐8DPF, and P7‐9DPF) toward deep‐blue polymer light‐emitting diodes (PLEDs). Compared to the highly crystalline capacity of P7DPF, P7‐8DPF, and P8DPF, alternative P7‐6DPF and P7‐9DPF present a feature and well‐resolved emission from a planar conformational segment of polyfluorene without obvious polaron features and charge transfer states. More interestingly, P7‐6DPF and P7‐9DPF show thickness‐independent electroluminescence (EL) behavior with a stable deep‐blue color purity, which is the precondition to fabricate large‐scale and high‐quality PLEDs. Finally, compared to control devices, PLEDs based on the P7‐6DPF and P7‐9DPF planar (β) conformational films present a well‐resolved and narrowband emission, stable EL spectra, high brightness (two‐ to threefold), and high current efficiency (1.3‐fold). Therefore, optimizing hierarchical structure via alternating copolymerization is an effective strategy to improve the performance and stability of deep‐blue PLEDs. [ABSTRACT FROM AUTHOR]

This study aimed to explore the specific effect of miR-200c in anaplastic thyroid cancer (ATC). Hth74 and ARO cell lines were used. Proliferation, invasion, and colony formation activities of Hth74 and ARO cell lines affected by miR-200c were studied. Expression of epithelial-to-mesenchymal transition (EMT) markers (E-cadherin, N-cadherin, Slug, and Snail) in the Hth74 and ARO cell lines were validated by western blot and qRT-PCR. In addition, the regulation of the parathyroid hormone-like hormone (PTHLH) by miR-200c was assessed. Overexpression of miR-200c inhibited the invasion, proliferation, and colony formation of the ATC cell lines, whereas its downregulation achieved the opposite results. PTHLH was found to be regulated negatively by miR-200c through a miR-200c binding site within the 3′-UTR of PTHLH. miR-200c repressed the proliferation, invasion, and EMT process of cells in ATC cell lines by targeting PTHLH post-transcriptionally, which indicates that miR-200c may be a potential target for the treatment of ATC. [ABSTRACT FROM AUTHOR]

Psoriasis is a chronic inflammatory skin disorder accompanied by excessive keratinocyte proliferation. Erianin (Eri) is an ideal drug candidate for inhibiting proliferation and inducing apoptosis in the treatment of psoriasis. However, Eri's poor water solubility and low penetration activity across the skin hinder its application in local medicine. In this study, we developed a novel photo-responsive dendritic mesoporous silica nanoparticle-based carrier to deliver erianin, improved its bioavailability, and achieved sustained-release effects. Spiropyran (SP), 3-aminopropyltriethoxysilane (APTES), and perfluorodecyltriethoxysilane (PFDTES) were conjugated to the outer surface, which allowed Eri to be released in response to UV radiation. The physicochemical properties of photo-responsive dendritic mesoporous silica nanoparticles (Eri-DMSN@FSP) were characterized via multiple techniques, such as using a Fourier-transform infrared spectrometer, a high-resolution transmission electron microscope, and nuclear magnetic resonance (NMR) spectroscopy. The anti-proliferative properties and light-triggered release of erianin-loaded photo-responsive dendritic mesoporous silica nanoparticles were assessed via the MTT assay and a drug release study in vitro. Erianin-loaded photo-responsive dendritic mesoporous silica nanoparticles (UV) exhibit a significantly enhanced HaCat cell-inhibiting efficacy compared to other formulations, as demonstrated by their extremely low cell viability of 10.0% (concentration: 500 mg/mL), indicating their capability to release a drug that responds to UV radiation. The cellular uptake of photo-responsive dendritic mesoporous silica nanoparticles (DMSN@FSP) was observed via confocal laser scanning microscopy (CLSM). These experimental results show that Eri-DMSN@FSP could be effectively endocytosed into cells and respond to ultraviolet light to release Eri, achieving a more effective psoriasis treatment. Therefore, this drug delivery system may be a promising strategy for addressing the question of Eri's delivery and psoriasis therapy. [ABSTRACT FROM AUTHOR]

Objective. The effect of the concept of enhanced recovery after surgery (ERAS) and pain of patients undergoing root canal therapy in oral clinic. Methods. 200 participants in an oral clinic from March 2020 to March 2022 were enrolled in our study. The control group (n = 100) accepted ERAS-based care and the research group (n = 100) accepted ERAS concept and cluster nursing. Nursing satisfaction, comfort, self-efficacy, subjective well-being, self-rating anxiety scale (SAS), and self-rating depression scale (SDS) scores were compared. Results. The research group had 100% satisfaction rate; the control group had 87% satisfaction rate. After nursing, the scores of comforts and self-efficacy of the two groups increased and the scores of comforts and self-efficacy of the research group were higher than those of the control group. After nursing, the scores of subjective well-being of the two groups increased. Furthermore, the higher scores of life satisfaction, interpersonal harmony, and self-efficacy in the research group were found. There was no significant difference in the scores of SAS and SDS between the two groups before nursing (P > 0.05), but after nursing, the scores of SAS and SDS in the two groups decreased, and the scores of SAS and SDS in the research group were lower than those in the control group, and there are statistically significant differences between the groups (P < 0.05). The scores of visual analogue score (VAS) and numerical rating scale (NRS) following intervention decreased, and there are statistically significant differences between the groups (P < 0.05). The less physiological, psychological, social functions, and health self-cognition in the research group were displayed, and there are statistically significant differences between groups (P < 0.05). Conclusion. The adoption of the concept of ERAS and cluster nursing can effectively improve the psychological state and pain score of oral outpatients undergoing root canal therapy, improve comfort and self-efficacy, and enhance subjective well-being and quality of life. ERAS and cluster nursing is of great significance in relieving pain after root canal therapy in the outpatient department, reducing patients' pain and improving patients' quality of life. [ABSTRACT FROM AUTHOR]

Existing multi-agent reinforcement learning methods employ a paradigm of centralized training with decentralized execution (CTDE) to learn cooperative policy among agents via coordination. However, within continuous destruction conditions, the inclusion of information from dead agents significantly undermines the ability to effectively learn cooperative policies in multi-agent systems. In this paper, we first analyze the bias introduced by dead agents under the CTDE paradigm and how it affects cooperation among agents. Following this, we propose q-learning based downsizing adaptive policy (QDAP) framework for cooperative multi-agent reinforcement learning. QDAP actively discerns relevant values from dead agents and utilizes an innovative approach to convert historical trajectories into weighting factors, thereby aiding remaining active agents in learning more appropriate cooperative policies. Moreover, we extend our proposed framework into the CTDE paradigm, facilitating seamless adaptation with the methods of value decomposition. Experimental results demonstrate that QDAP significantly improves learning speed and achieves superior cooperation performance on challenging Starcraft II micromanagement benchmark tasks. [ABSTRACT FROM AUTHOR]

Lung cancer has a higher incidence and mortality rate than other cancers, and over 80% of lung cancer cases were classified as non-small-cell lung cancer (NSCLC). TRIM66 is one of the crucial members of TRIM, which has a deep connection with the behavior of various malignant tumors. But it remains uncertain regarding its exact function and underlying mechanism in NSCLC. In our study, qRT-PCR and Western blot were employed to validate that TRIM66 was overexpressed in NSCLC. The migration, invasion, and epithelial-mesenchymal transformation (EMT) progression of NSCLC cells were determined by Western blotting and Transwell experiments after knocking down TRIM66, and it was found that knockdown TRIM66 inhibited the migration, invasion, and EMT processes of NSCLC cells. Next, the binding relationship between TRIM66 and MMP9 was verified by Co-IP assay. After determining the interaction between them, rescue assays showed that overexpression of MMP9 was capable to promote the migration, invasion, and EMT of NSCLC cells. However, the transfection of si-TRIM66 could reverse this facilitating effectiveness. To sum up, we concluded that by targeting MMP9, TRIM66 could exert a cancer-promoting role in the progression of NSCLC cells. [ABSTRACT FROM AUTHOR]

Dehydrins, also known as Group II late embryogenesis abundant (LEA) proteins, are classic intrinsically disordered proteins, which have high hydrophilicity. A wide range of hostile environmental conditions including low temperature, drought, and high salinity stimulate dehydrin expression. Numerous studies have furnished evidence for the protective role played by dehydrins in plants exposed to abiotic stress. Furthermore, dehydrins play important roles in seed maturation and plant stress tolerance. Hence, dehydrins might also protect plasma membranes and proteins and stabilize DNA conformations. In the present review, we discuss the regulatory networks of dehydrin gene expression including the abscisic acid (ABA), mitogen-activated protein (MAP) kinase cascade, and Ca2+ signaling pathways. Crosstalk among these molecules and pathways may form a complex, diverse regulatory network, which may be implicated in regulating the same dehydrin. [ABSTRACT FROM AUTHOR]

Recently, the all- d -metal Ni(Co)MnTi based Heusler compounds are found to have a giant magnetocaloric effect (GMCE) near room temperature and manifest different functionalities like multicaloric effects, which can be employed for solid-state refrigeration. However, in comparison to other traditional Heusler compounds, the relatively large thermal hysteresis (ΔT hys) and moderately steep ferromagnetic phase transition provides limitations for real applications. Here, we present that fast solidification (suction casting) can sufficiently tailor the GMCE performance by modifying the microstructure. Compared with the arc-melted sample, the magnetic entropy change of the suction-casted sample shows a 67% improvement from 18.4 to 29.4 Jkg−1K−1 for a field change (∆ μ 0 H) of 5 T. As the thermal hysteresis has maintained a low Δ T hys value (5.5 K) for the enhanced first-order phase transition, a very competitive reversible magnetic entropy change of 21.8 Jkg−1K−1 for ∆ μ 0 H = 5 T is obtained. Combining high-resolution transmission electron microscopy (HRTEM) and positron annihilation spectroscopy (PAS) results, the difference in lattice defect concentration is found to be responsible for the significant improvement in GMCE for the suction-cast sample, which suggests that defect engineering can be applied to control the GMCE. Our study reveals that fast solidification can effectively regulate the magnetocaloric properties of all- d -metal NiCoMnTi Heusler compounds without sacrificing Δ T hys. [Display omitted] [ABSTRACT FROM AUTHOR]

Purpose: Intergroup contact is an effective strategy to improve intergroup relationships. Although intergroup relationships have been studied extensively, the individual roles of quantity and quality of contact in relationships with cognition, emotion, and intention of behavior toward other ethnic minority groups are not fully understood. This study explores the situation via network analysis among Zhuang and Yao ethnic minorities in Southwest China. Methods: We investigated the quantity and quality of intergroup contact and cognition, emotion, and intention of behavior among a sample of 543 Zhuang and 490 Yao ethnic group members. Data were analyzed using the R-package. Network structures were analyzed via the Qgraph package, and the accuracy and stability of the network were measured via the Bootnet package; communities were detected via the Igraph package; bridge analyses were conducted via the Networktools package; and the network difference was compared via the Network Comparison Test package. Results: The results indicated perceived intimacy is the central node. Quantity of contact constructed a community with "perceived connection," "sense of community," "knowledge about out-group," and "perceived similarity." Meanwhile, quality of contact constructed a community with "intergroup attitude" and a "feeling thermometer." The remainder of the nodes constructed two additional communities. The network global connectivity and structure between the two ethnic groups were highly similar. Conclusion: The study examined the quantity and quality of intergroup contact via network analysis for two ethnic minority groups. It was shown that the two groups' global network structures of intergroup contact and their effects are highly similar. Specifically, quantity and quality of contact produce different effects on intergroup relations. Quantity of contact has proximal effects, including instant cognitive and emotional response without depth cognition, while quality of contact has proximal effects that may change deep-seated cognition and subsequently improve intergroup relations. [ABSTRACT FROM AUTHOR]

To determine the influence of preoperative prognostic nutritional index in adenocarcinoma of the esophagogastric junction, this study was conducted to analyze 420 patients with adenocarcinoma of the esophagogastric junction who underwent surgery. A total of 120 healthy volunteers were included as the healthy control group. The cutoff values of prognostic nutritional index for predicting survival were obtained according to the receiver operating characteristic curve. The clinic-pathological feature and survival were compared between low and high prognostic nutritional index group. Results showed that the prognostic nutritional index in the patient group was lower than that in the healthy control group (P < 0.05). The level of prognostic nutritional index was significantly associated with tumor differentiation, Siewert type, tumor size, body mass index, and hemoglobin levels (P < 0.05). The level of prognostic nutritional index was negatively correlated with age of onset, tumor differentiation, Siewert type, tumor size, depth of tumor, but positively associated with the levels of body mass index and hemoglobin. Multivariate analysis revealed that prognostic nutritional index was an independent factor associated with disease-free survival (P = 0.027) and overall survival (P = 0.003). In conclusion, low prognostic nutritional index may be considered as an independent adverse prognostic marker in patients with adenocarcinoma of the esophagogastric junction. [ABSTRACT FROM AUTHOR]

This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), better known as COVID-19, has become a current threat to humanity. The second wave of the SARS-CoV-2 virus has hit many countries, and the confirmed COVID-19 cases are quickly spreading. Therefore, the epidemic is still passing the terrible stage. Having idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD) are the risk factors of the COVID-19, but the molecular mechanisms that underlie IPF, COPD, and CVOID-19 are not well understood. Therefore, we implemented transcriptomic analysis to detect common pathways and molecular biomarkers in IPF, COPD, and COVID-19 that help understand the linkage of SARS-CoV-2 to the IPF and COPD patients. Here, three RNA-seq datasets (GSE147507, GSE52463, and GSE57148) from Gene Expression Omnibus (GEO) is employed to detect mutual differentially expressed genes (DEGs) for IPF, and COPD patients with the COVID-19 infection for finding shared pathways and candidate drugs. A total of 65 common DEGs among these three datasets were identified. Various combinatorial statistical methods and bioinformatics tools were used to build the protein–protein interaction (PPI) and then identified Hub genes and essential modules from this PPI network. Moreover, we performed functional analysis under ontologies terms and pathway analysis and found that IPF and COPD have some shared links to the progression of COVID-19 infection. Transcription factors–genes interaction, protein–drug interactions, and DEGs-miRNAs coregulatory network with common DEGs also identified on the datasets. We think that the candidate drugs obtained by this study might be helpful for effective therapeutic in COVID-19. [ABSTRACT FROM AUTHOR]

This work presented a novel net-shape-forming technology to prepare oxide dispersion strengthened (ODS) copper by cold spray additive manufacturing. There were three types of Al 2 O 3 particles in the internal oxidation Cu-Al 2 O 3 raw powders. After cold spraying, two types of nano-sized Al 2 O 3 inside the raw powder were inherited into the deposition, and the micro-sized Al 2 O 3 on the powder surface was crushed to nano-size under severe plastic deformation, which dispersed along the interface of deformed powder due to the plastic flow of Cu caused by adiabatic shearing. The plastic deformation produced by cold spraying was 20% higher than the hot extrusion with extrusion ratio of 11:1, which fully achieves the Al 2 O 3 fragmentation, dispersion distribution and densification of the cold sprayed deposition. Moreover, due to the significant work hardening and grain refinement effect by SPD during cold spraying, Vickers hardness and nanoindentation hardness of the ODS Cu deposition increased to 185.63 HV 3 and 2.76 GPa, respectively, which were significantly higher than the raw powders and hot extrusion sample. • The net-shape-forming of large-scale ODS Cu was fabricated by cold spray additive manufacturing. • ODS Cu deposition exhibited significant grain refinement and work hardening effect. • Nano-sized Al 2 O 3 particles inherited to the deposition. • Large-sized Al 2 O 3 particles broke due to the severe plastic deformation. [ABSTRACT FROM AUTHOR]

• The correlation analysis method is proposed to verify the MAS effect in the recording process. • It is confirmed that the medium-dependent gain corresponds to the FMR frequency change between the media. • This is the world's first report on the quantification of the MAS effect in the recording process. Frequency matching is the most important key point for designing microwave-assisted switching (MAS) and microwave-assisted magnetic recording (MAMR). It is necessary to quantitatively compare an assist effect by MAS (MAS effect) of some media when designing and optimizing a medium from the viewpoint of frequency matching experimentally. However, it is difficult to directly compare the MAS effect between media because the differences in the resolution and saturation characteristics of the medium strongly influence the recording properties. In this study, we propose a new method for appropriately removing these effects other than the MAS effect by evaluating the relationship of recording characteristics between media. By using this method, the difference of the MAS effect between any media can be quantitatively compared and used as an index for medium design to optimize MAMR. [ABSTRACT FROM AUTHOR]

Hard Disk Drive read heads moved from GMR to Tunneling Magnetoresistive (TMR) Devices as a way to enhance head SNR in order to keep up with advanced linear densities. TMR technology was further extended by the transition from amorphous alumina tunneling barriers to crystalline MgO barriers lattice matched to adjacent BCC magnetic layers resulting in much higher MR ratios. Enhanced side shielding using Junction Shield and reduced shield to shield spacing were additional enablers that increased track and linear density capabilities of TMR heads. TMR heads gained additional momentum and complexity by the introduction of two dimensional recording heads that boosted head SNR by up to 3 dB. As the RA of the tunneling barriers is reduced, overcoming spin torque noise presents itself as a further challenge to be addressed. As device dimensions are scaled down, magnetic thermal noise can only be overcome by increasing the moment of the free layer which may already start establishing the final density point achievable by TMR heads. [ABSTRACT FROM AUTHOR]

[Display omitted] • Baicalein-loaded mPEG-PLGA nanoparticles with a high drug-loading rate and stability were developed, which has high biocompatibility and low toxicity. • Baicalein enables to inhibition of the TGF-β/Smad and TGF-β/MAPK signaling pathways and reduces the activation of cancer associated fibroblasts. • PMs-Ba could remodel the tumor microenvironment by baicalein-loaded mPEG-PLGA, contributing to enhancing the anti-tumor impact of adriamycin-loaded mPEG-PLGA. Cancer-associated fibroblasts constitute a significant component in the tumor microenvironment, playing a pivotal role in tumor proliferation, invasion, migration, and metastasis. Consequently, therapy combining chemotherapeutic agents with tumor microenvironment (TME) modulators appears to be a promising avenue for cancer treatment. In this paper, a tumor microenvironment-based mPEG-PLGA nanoparticle loaded with baicalein (PMs-Ba) was constructed for the purpose of improving the tumor microenvironment in cases of triple-negative breast cancer. The results demonstrate that, on the one hand, PMs-Ba was able to inhibit the transforming growth factor β(TGF-β) signaling pathway to avoid the activation of cancer-associated fibroblasts (CAFs), thereby influencing the interstitial microenvironment of the tumor. On the other hand, the agent led to an increase in the infiltration of cytotoxic T cells, activating the tumor immune microenvironment. Meanwhile, in the murine breast cancer model, an intravenous injection of PMs-Ba combined with doxorubicin nanoparticles (PMs-ADM) significantly improved the antitumor effectiveness. These results suggest that baicalein encapsulated in nanoparticles may be a promising strategy for modulating the TME and for adjuvant chemotherapy, signifying a potential TME-remodeling nanoformulation that could enhance the antitumor efficacy of nanotherapeutics. [ABSTRACT FROM AUTHOR]

The VOx films with composition from metal-rich to maximum stoichiometry can be accessed by tuning the pulse frequency, without varying any other parameters, especially, the flow rate of reactive gas. With the increase of pulse frequency, which can also facilitate the formation of a denser microstructure and smoother surface morphology in the films. The temperature dependent electrical properties of the VOx films can also be tailored via pulse frequency in a wide range to satisfy specific applications, such as microbolometer. [Display omitted] • • VOx films were prepared by reactive pulsed DC magnetron sputtering. • • The role of pulse frequency on the deposition process and properties of VOx films were investigated. • • Composition and some important properties of VOx films can be tailored by pulse frequency effectively. • • The corresponding underlying mechanisms were discussed in detail. In this study, vanadium oxide (VOx) thin films were prepared by reactive pulsed DC magnetron sputtering (PDMS). The influence of pulse frequency (F p) on the deposition process and properties of VOx films was investigated. The obtained results indicate that with the increase of F p , which not only can enhance the oxidation of vanadium but also can facilitate the formation of a denser microstructure and smoother surface morphology in the films. More importantly, films with composition from metal-rich to maximum stoichiometry can be accessed by tuning the F p , without varying any other parameters, especially, the flow rate of reactive gas. And temperature dependent electrical properties of the VOx films can also be tailored via the F p to fall in the desirable range for microbolometer applications. The impacts of F p on the reaction between V and O, thin film growth and some dynamic processes occurring during reactive PDMS were analyzed. The corresponding underlying mechanisms were discussed in detail. Our present work may provide a practical and effective way to develop the reactive sputtering towards hysteresis-free, and also paves the way for optimizing the reactive sputtered VOx films with desirable properties via F p. [ABSTRACT FROM AUTHOR]