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We propose a strategy for magnetic navigation of collective stem cell microrobots in blood environments under ultrasound Doppler imaging. The cell microrobots are fabricated through a coculture process of stem cells and iron microparticles, they have spheroidal structures and are actuated under external magnetic fields. The collective cell microrobots can be reversibly gathered and spread by adjusting the magnetic interaction, and these microrobots are able to exhibit collective motion in whole blood under rotating magnetic fields. Simulation results indicate that the induced blood flow around the collective pattern affects the motion of red blood cells, and experimental results show that Doppler signals are observed when emitting ultrasound waves to the microrobots. Due to the induced three-dimensional blood flow, Doppler signals can also be observed when the imaging plane is above the collective microrobots, which enables indirect localization when performing navigation on uneven surfaces. Moreover, collective patterns of different numbers of microrobots are formed in flowing conditions, and these collective biohybrid agents are actively navigated against flowing blood with a flow rate up to 4.5 mL/min (mean velocity: 5.97 mm/s). Our study investigates a strategy for pattern formation and navigation of collective microrobots under ultrasound Doppler imaging, demonstrating the integration of collective control approach and medical imaging holds great potential for real-time active delivery tasks.

In the era of social networks, the rapid growth of data mining in information retrieval and natural language processing makes automatic text summarization necessary. Currently, pretrained word embedding and sequence to sequence models can be effectively adapted in social network summarization to extract significant information with strong encoding capability. However, how to tackle the long text dependence and utilize the latent topic mapping has become an increasingly crucial challenge for these models. In this article, we propose a topic-aware extractive and abstractive summarization model named T-BERTSum, based on Bidirectional Encoder Representations from Transformers (BERTs). This is an improvement over previous models, in which the proposed approach can simultaneously infer topics and generate summarization from social texts. First, the encoded latent topic representation, through the neural topic model (NTM), is matched with the embedded representation of BERT, to guide the generation with the topic. Second, the long-term dependencies are learned through the transformer network to jointly explore topic inference and text summarization in an end-to-end manner. Third, the long short-term memory (LSTM) network layers are stacked on the extractive model to capture sequence timing information, and the effective information is further filtered on the abstractive model through a gated network. In addition, a two-stage extractive-abstractive model is constructed to share the information. Compared with the previous work, the proposed model T-BERTSum focuses on pretrained external knowledge and topic mining to capture more accurate contextual representations. Experimental results on the CNN/Daily mail and XSum datasets demonstrate that our proposed model achieves new state-of-the-art results while generating consistent topics compared with the most advanced method.

Nowadays, mining opinion or sentiment from the online user-generated texts has become a research hot-spot. Although, a large amount of lexicon-based Chinese polarity detection works have been done, yet the existing methods have one common flaw that even the same word can have opposite polarities among different seed-lexicons, or polarity fuzziness. Therefore, in order to further enhance the performance of Chinese sentiment polarity detection, in this paper, we start from a two-aspect lexicon expansion, specifically, detecting sentiment polarity for new words and revising sentiment polarity for words already defined in seed-lexicons, so that the polarity fuzziness can be avoided. Then, we formulate a novel sentiment polarity detection framework for Chinese (SPDFC) with more effort to fine-grained sentiment processing, involved in symmetrical mapping, sentiment feature pruning and text representation. In this way, the word polarity can be directly taken as features, further penetrating into polarity detection phase. According to the experimental results, compared to other classical and state-of-the-art methods, the proposed the framework SPDFC can achieve the best overall performance from the perspective of Chinese polarity detection, sentiment feature pruning as well as text representation.

Background and aims Stress is a common experience among college students with problematic Internet use, and it may exacerbate their cue-induced Internet craving. This study aimed to examine the influence of stress on cue-induced craving for the Internet among subjects with problematic Internet use and the buffering effect of mindfulness. Methods Sixty-eight college students with problematic Internet use were assigned to groups with a 2 (stress vs. no-stress) × 2 (high vs. low mindfulness) between-subject design. Results It was deduced that stress could significantly enhance cue-induced craving for the Internet, and mindfulness could buffer this effect. Specifically, the effect of stress on cue-induced craving for the Internet was weaker among subjects with high mindfulness as compared to subjects with low mindfulness. Discussion and Conclusions These findings contribute to understanding of the factors influencing problematic Internet use and how such factors interact. It also provides recommendations on how to prevent the progression of problematic Internet use and suggests possible interventions.

Objective Accurate analysis to quantify cartilage morphology is critical for evaluating degenerative conditions in osteoarthritis (OA). Three-dimensional (3D) optical scanning provides 3D data for the entire cartilage surface; however, there is no consensus on how to quantify it. Our purpose was to validate a 3D method for evaluating spatiotemporal alterations in degenerative cartilages in a rabbit OA model by analyzing their curvatures at various stages of progression. Design Twelve rabbits underwent anterior cruciate ligament transection (ACLT) unilaterally and were divided into 4 groups: 4 weeks control, 4 weeks OA, 8 weeks control, and 8 weeks OA. 3D scanning, India ink staining, and histological assessments were performed in all groups. In 3D curvature visualization, the surfaces of the condyles were divided into 8 areas. The standard deviations (SD) of mean curvatures from all vertices of condylar surfaces and subareas were calculated. Results Regarding the site of OA change, curvature analysis was consistent with India ink scoring. The SD of mean curvature correlated strongly with the India ink Osteoarthritis Research Society International (OARSI) score. In curvature histograms, the curvature distribution in OA was more scattered than in control. Of the 8 areas, significant OA progression in the posterolateral part of the lateral condyle (L-PL) was observed at 4 weeks. The histology result was consistent with the 3D evaluation in terms of representative section. Conclusions This study demonstrated that 3D scanning with curvature analysis can quantify the severity of cartilage degeneration objectively. Furthermore, the L-PL was found to be the initial area where OA degeneration occurred in the rabbit ACLT model.

Industrial agglomeration (IA) has greatly promoted the improvement of industrial efficiency (IE), but it has also brought serious environmental pollution (EP), which in turn affects sustainable industrial development. Therefore, this study built a theoretical derivation model including pollution output and used a vector error correction model (VECM) and three-stage simultaneous equations (3SLS) to explore the mechanisms among IA, EP and sustainable IE. The following conclusions were reached: (1) The relationship between IA and EP presents an inverted U-shape and is located on the left side of the inverted U-shape curve. IA has increased emissions of industrial sulphur dioxide, industrial soot and industrial wastewater pollutants, but is conducive to IE. Increased EP will inhibit both IA and the level of IE. (2) Both IA and low EP can enhance the level of sustainable IE. (3) IE plays a mitigating role in IA and EP; it will weaken the inhibitory effect of EP on IA and strengthen the impact of IA on EP. In the future, China should continue its industrialization process to promote the scale of IA and strictly control the discharge of industrial pollutants to reduce EP. Simultaneously, the government should encourage industrial enterprises to improve technological innovation to promote IE. IA, EP and IE form a virtuous circle that promotes the development of the industrial economy and optimizes the environment. This approach can also be applied to other regions to provide decision support for the sustainable development of industry.

Background Non-coplanar volumetric modulated arc therapy (ncVMAT) is proposed to reduce toxicity in heart and lungs for locoregional radiotherapy of left-sided breast cancer, including internal mammary nodes (IMN). Patients and methods This retrospective study included 10 patients with left-sided breast cancer who underwent locoregional radiotherapy after breast-conserving surgery. For each patient, the ncVMAT plan was designed with four partial arcs comprising two coplanar arcs and two non-coplanar arcs, with a couch rotating to 90°. The prescribed dose was normalized to cover 95% of planning target volume (PTV), with 50 Gy delivered in 25 fractions. For each ncVMAT plan, dosimetric parameters were compared with the coplanar volumetric modulated arc therapy (coV-MAT) plan. Results T here were improvements in conformity index, homogeneity index and V55 of total target volume (PTVall) comparing ncVMAT to coVMAT (p < 0.001). Among the organs at risk, the average V30, V20, V10, V5, and mean dose (Dmean) of the heart decreased significantly (p < 0.001). Furthermore, ncVMAT significantly reduced the mean V20, V10, V5, and Dmean of left lung and the mean V10 and V5 and Dmean of contralateral lung (p < 0.001). An improved sparing of the left anterior descending coronary artery and right breast were also observed with ncVMAT (p < 0.001). Conclusions Compared to coVMAT, ncVMAT provides improved conformity and homogeneity of whole P TV, better dose sparing of the heart, bilateral lungs, left anterior descending coronary artery (LAD), and right breast for locoregional radiotherapy of left-sided breast cancer with IMN, potentially reducing the risk of normal tissue damage.

Facing the rapid expansion of the sharing economy, it is essential to understand the trusting mechanism in the P2P sector and its consequence on the perceived risks. This study extends the elaborat...

Cytotoxic T cells expressing cell surface CD8 played a key role in anti-cancer immunotherapy, including kidney renal clear cell carcinoma (KIRC). Here we set out to comprehensively analyze and evaluate the significance of CD8+ T cell-related markers for patients with KIRC. We checked immune cell response in KIRC and identified cell type-specific markers and related pathways in the tumor-infiltrating CD8+ T (TIL-CD8T) cells. We used these markers to explore their prognostic signatures in TIL-CD8+ T by evaluating their prognostic efficacy and group differences at various levels. Through pan-cancer analysis, 12 of 63 up-regulated and 162 of 396 down-regulated genes in CD8+ T cells were found to be significantly correlated with the survival prognosis. Based on our highly integrated multi-platform analyses across multiple datasets, we constructed a 6-gene risk scoring model specific to TIL-CD8T. In this model, high TIL-CD8 sig score was corresponding to a higher incidence frequency of copy number variation and drug sensitivity to sorafenib. Moreover, the prognosis of patients with the same or similar immune checkpoint gene levels could be distinguished from each other by TIL-CD8 sig score.

Astragali radix (AR, the dried root of Astragalus) is a popular herbal remedy in both China and the United States. The commercially available AR is commonly classified into premium graded (PG) and ungraded (UG) ones only according to the appearance. To uncover novel sensitive and specific markers for AR grading, we took the integrated mass spectrometry-based untargeted and targeted metabolomics approaches to characterize chemical features of PG and UG samples in a discovery set (n=16 batches). A series of five differential compounds were screened out by univariate statistical analysis, including arginine, calycosin, ononin, formononetin, and astragaloside Ⅳ, most of which were observed to be accumulated in PG samples except for astragaloside Ⅳ. Then, we performed machine learning on the quantification data of five compounds and constructed a logistic regression prediction model. Finally, the external validation in an independent validation set of AR (n=20 batches) verified that the five compounds, as well as the model, had strong capability to distinguish the two grades of AR, with the prediction accuracy > 90%. Our findings present a panel of meaningful candidate markers that would significantly catalyze the innovation in AR grading., Graphical abstract Image 1, Highlights • Five specific and reliable markers are uncovered to distinguish two grades of AR. • A logistic regression prediction model is built, with an accuracy of > 90%. • Most markers, but not astragaloside Ⅳ, exhibit accumulation in premium graded AR. • The findings are validated in an independent set by targeted LC-MS/MS analysis.

BACKGROUND: The significance of nano-carbon for lymph node staging in radical gastrectomy for gastric cancer (GC) has been confirmed, but studies on its application for GC patients treated with neoadjuvant chemotherapy (NCT) are rare. The purpose of this study was to explore the clinical value of using carbon nanoparticles suspension injections (CNS) to improve the accuracy of lymph node staging (N staging) of NCT for advanced GC. METHODS: 160 advanced GC patients receiving preoperative NCT were enrolled, according to the random number generated by computer, the enrolled patients were randomly divided into two groups: experimental group (n=80) and control group (n=80). The experimental group received endoscopic injection of CNS within 24 hours prior to NCT, while the control group received this within 24 hours post NCT and before D2 radical resection. SOX [oxaliplatin: 130 mg/(body surface area, BSA): m(2), first day + S-1: (BSA

The study aims to compare the efficacies of the immunosuppressants most commonly prescribed for patients with neuromyelitis optica spectrum disorder (NMOSD). The predictors, which might be associated with relapse and disability in NMOSD, were also analyzed. This retrospective study included NMOSD patients treated with azathioprine (AZA), mycophenolate mofetil (MMF), and rituximab (RTX). The annual relapse rate (ARR) and the incidence rates of adverse events were compared. Cox proportional-hazards model calculated the potential predictors of NMOSD relapse and disability. A total of 83 patients were included. The median treatment time of AZA group (n = 34), MMF group (n = 20), and RTX group (n = 29) were 19.5, 15.5, and 12 months, respectively. ARR of the three groups reduced significantly after treatment. In the three groups, 55.9%, 50%, and 79.3% of patients, respectively, were free from relapse. However, the difference among the three groups was of no statistical significance, possibly due to the small sample size. During the treatment, 32.4%, 15%, and 24.1% of patients experienced adverse events in the AZA group, MMF group, and RTX group, respectively. Additionally, the multivariate Cox analyses indicated that history of a severe attack and disease duration were associated with the risk of relapse after immunotherapy. Late-onset (≥ 50 years old) NMOSD patients were probably more susceptible to motor disability, and those with optic neuritis at onset were more likely to develop visual disability. AZA, MMF, and low-dose RTX were all effective in reducing the relapse rate in NMOSD. The age at onset, disease duration, history of severe attacks, and primary syndromes might be significant prognostic predictors in NMOSD.

The aim of this study was to compare the functional characteristics of mesenchymal stromal cells (MSCs) from a sheep model of traumatic temporomandibular joint (TMJ) fibrous and bony ankylosis. A sheep model of bilateral TMJ trauma-induced fibrous ankylosis on one side and bony ankylosis on the contralateral side was used. MSCs from fibrous ankylosed callus (FA-MSCs) or bony ankylosed callus (BA-MSCs) at weeks 1, 2, 4, and 8 after surgery were isolated and cultured. MSCs derived from the bone marrow of the mandibular condyle (BM-MSCs) were used as controls. The MSCs from the different sources were characterized morphologically, phenotypically, and functionally. Adherence and trilineage differentiation potential were presented in the ovine MSCs. These cell populations highly positively expressed MSC-associated specific markers, namely CD29, CD44, and CD166, but lacked CD31 and CD45 expressions. The BA-MSCs had higher clonogenic and proliferative potentials than the FA-MSCs. The BA-MSCs also showed higher osteogenic and chondrogenic potentials, but lower adipogenic capacity than the FA-MSCs. In addition, the BA-MSCs demonstrated higher chondrogenic, but lower osteogenic capacity than the BM-MSCs. Our study suggests that inhibition of the osteogenic and chondrogenic differentiations of MSCs might be a promising strategy for preventing bony ankylosis in the future.

Academic adaptation is an important aspect of children’s development, and it has been found to be closely associated with parent and peer related factors. In the current information era, the internet is also influencing children’s academic adaptation. Against this backdrop, we developed and tested a model in which active parental internet mediation (parents’ guidance and advice on children’s online behavior) was associated with children’s academic adaptation, further investigating the potential mediating role of video gaming and the moderating role of deviant peer affiliation. 683 Chinese elementary school students in Grades 4–6 were recruited to participate in this study. The children completed questionnaires at school during regular class time. The results indicated that: (a) after controlling for gender and age, active parental mediation was positively associated with academic adaptation; (b) video gaming was an mediating factor in the association between active parental mediation and academic adaptation; (c) the indirect effect of active parental mediation on academic adaptation through video gaming was moderated by deviant peer affiliation; specifically, for children with low deviant peer affiliation, the association between video gaming and academic adaptation was significant but insignificant for children with high deviant peer affiliation. Though, the relative small effect size of video gaming should be examined in the future studies to further clarify the associations and underlying mechanism between the main variables, the results have applied value for guiding children to use the internet responsibly and improving their academic adaptation.

BACKGROUND: To explore the efficacy and safety of neoadjuvant intraperitoneal and systemic (NIPS) paclitaxel chemotherapy combined with apatinib and S-1 in the treatment of gastric cancer patients with positive exfoliative cytology. METHODS: Patients with gastric cancer (P(0)CY(1)) who were confirmed to have free cancer cells (FCCs) in the abdominal cavity after laparoscopic exploration from April 2018 to August 2019 were enrolled. All patients underwent NIPS chemotherapy using paclitaxel combined with apatinib and S-1 treatment. Laparoscopic exploration was performed after 3 cycles of conversion therapy. The primary study endpoint was the FCC negative rate, and the secondary study endpoints were overall survival time (OS), progression-free survival time (PFS), objective response rate (ORR), disease control rate (DCR), and safety indicators. RESULTS: Out of 312 advanced gastric cancer patients who underwent laparoscopic exploration, 36 patients with P(0)CY(1) gastric cancer were identified and enrolled in this study. After 3 cycles of conversion therapy, the ORR was 80.56% and the DCR was 94.44%. All patients underwent secondary laparoscopic exploration, and the FCC conversion rate was 77.78%. All patients with negative FCC underwent R0 surgical resection, with a median follow-up time of 11.4 months. The median survival time was 15.5 months, and the 1-year OS was 80.55%. The median PFS was 14.4 months, and the 1-year PFS was 75.00%. Treatment-related grade 3 adverse reactions were mainly leukopenia and neutropenia. No grade 4 adverse reactions were observed. There were no reported deaths related to chemotherapy or surgery in the study cohort. CONCLUSIONS: NIPS with paclitaxel combined with apatinib and S-1 treatment may increase the FCC negative rate of P(0)CY(1) gastric cancer patients.

Social media has recently become one of the most used media in the world. This has resulted in a great hotbed for the growth of rumors, as anyone can spread knowledge and opinions without confirmation. Previous works on rumor detection focused on hand-extracted features and spent less effort on text representation. In this research, a novel method for rumor detection on social media is proposed, which integrates entity recognition, sentence reconfiguration and ordinary differential equation network under a unified framework called ESODE. An entity recognition method to enhance the semantic understanding of rumor texts is used. Then, a sentence reconfiguration to improve the frequency of important words is designed. The complete feature map is established by further collecting statistical features from three aspects: linguistic features on the content of rumors, characteristics of users involved in rumor propagating, and propagation network structures. Finally, the ordinary differential equation network (ODEnet) is applied to detect rumors. Experimental results on datasets from Twitter and Weibo show that the proposed method achieves better performance than previous ones.

Under the constraints of resources and the environment, exploring the channels to improve the quality of China’s economy is very important for China’s current sustainable development. Therefore, this paper studies whether innovation can improve the quality of China’s economy and explore the path of sustainable development from the perspective of the city. Based on the Malmquist–Luenberger index and DEA-Malmquist index, this paper, respectively, measures the green total factor productivity (GTFP) and total factor productivity (TFP) of 193 cities in China. On the basis of obtaining the GTFP, TFP, and various pollutant emissions of 193 cities, this paper selects environmental regulations as the threshold variable and the number of urban patents as the explanatory variable to measure the level of urban innovation. On this basis, we examine the impact of innovation quality on economic quality and environmental pollution under different environmental regulatory intensities. The research results show that the impact of innovation on GTFP and TFP under different environmental regulations is always positive, but the impact coefficient and significance level vary. In addition, the impact of innovation on SO2 emissions under different environmental regulations has also changed. With the increase of environmental regulations, the effect of reducing emissions is gradually significant. The conclusion of this paper better interprets the development of TFP and GTFP under the innovation-driven strategy, provides a decision-making basis for departments at all levels to formulate innovation support policies, and explores the path of sustainable development.

Background There is a lack of comparative analyses on the use of carbon nanoparticle suspension injection (CNSI) and indocyanine green (ICG) tracer technology for lymph node detection and their perioperative safety in robotic radical gastrectomy. Methods A retrospective analysis was performed on patients who underwent robotic distal gastrectomy between November 2019 and November 2020. Patients were assigned to the CNSI group, the ICG group, or the control group. The number of lymph nodes detected, number of lymph nodes detected at each station, number of micro lymph nodes detected, rate of lymph node metastasis, and inoperative and postoperative recovery were compared. Results Of the 93 patients analyzed, 34 were in the CNSI group, 27 were in the ICG group, and 32 were in the control group. The mean number of lymph nodes retrieved in the CNSI group (48.44) was higher than that in the ICG (39.19) and control (35.28) groups (P = 0.004; P P = 0.102). The mean number of micro lymph nodes retrieved in the CNSI group (13.24) was higher than that in the ICG (5.74) and control (5.66) groups (P P > 0.05). Conclusion The effect of CNSI on lymph node dissection and sorting was better than that of ICG, and CNSI improved the surgical quality and reduced lymph node staging deviation to a greater extent. CNSI was better than ICG in terms of improving the number of micro lymph nodes detected.

Traditional alloy design which requires deep understanding of the Process–Structure–Property relationship, involves numerous tests and iterations. It is not cost-effective and very time-consuming. Current study explored the idea of using machine learning to build quantitative models to predict creep life of Cr–Mo steel with the help of convention creep study wisdom. Three time–temperature parameters, namely Larson-Miller parameter (LMP), Manson-Haferd parameter (MHP) and Manson-Succop parameter (MSP), were used as the target feature instead of creep life. Moreover, Pearson correlation coefficient (PCC) and Spearman correlation coefficient (SCC) were used to discuss the feature importance of creep life. The results demonstrated that the prediction accuracy was effectively improved by transforming creep life into LMP, MHP and MSP. In the case of using MSP as target feature, random forest (RF) had the best accuracy and robustness in all regression models. Feature importance ranking provided new insights for domain experts to analyze the main influencing features to creep property of Cr–Mo steel. This study has successfully proved the feasibility of combining machine learning and time–temperature parameters in predicting creep life and provided a basic idea and workflow for researchers to predict creep life of steel.

Editor’s notes: A group of academicians from the University of Virginia has developed a graduate curriculum for cyber-physical systems education. The curriculum follows the National Academy of Engineering report on the need for such content consisting of multidisciplinary classes and professional development skills. — Mohammad Abdullah Al Faruque, University of California Irvine

Due to its effectiveness, cancer immunotherapy has attracted widespread attention from clinicians and scientific researchers. Numerous studies have proven that effective stratification of cancer patients would promote the personalized application of immunotherapy. Therefore, we used the transcriptome data of nearly 1,000 patients with non-small cell lung cancer (NSCLC) to construct a new immune subgroup. We found that the new immune subgroup, named cluster 2, was a mixture of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), and showed poor overall survival, which was further verified in the independent validation set. Immune infiltration correlation analysis showed that the Mast cell type and its status subdivisions had a predictive effect on the prognosis of NSCLC, especially in LUAD. Phenotypic analysis suggested that epithelial-mesenchymal transition (EMT) was positively correlated with immunosuppression, supporting the correlation between tumor phenotype and immune background. Although immune subtypes failed to significantly distinguish the progression-free survival (PFS) of immunotherapy patients, they showed the expected trend; the sample size needs to be further expanded for verification. In addition, some results indicated that the two cancer types, LUAD and LUSC, might require independent analyses.

The typical aim of user matching is to detect the same individuals cross different social networks. The existing efforts in this field usually focus on the users' attributes and network embedding, but these methods often ignore the closeness between the users and their friends. To this end, we present a friend closeness based user matching algorithm (FCUM). It is a semi-supervised and end-to-end cross networks user matching algorithm. Attention mechanism is used to quantify the closeness between users and their friends. We considers both individual similarity and their close friends similarity by jointly optimize them in a single objective function. Quantification of close friends improves the generalization ability of the FCUM. Due to the expensive costs of labeling new match users for training FCUM, we also design a bi-directional matching strategy. Experiments on real datasets illustrate that FCUM outperforms other state-of-the-art methods that only consider the individual similarity.

Amyloid-β (Aβ) accumulation in the brain is a pivotal event in the pathogenesis of Alzheimer's disease (AD), and its clearance from the brain is impaired in sporadic AD. Previous studies suggest that approximately half of the Aβ produced in the brain is cleared by transport into the periphery. However, the mechanism and pathophysiological significance of peripheral Aβ clearance remain largely unknown. The kidney is thought to be responsible for Aβ clearance, but direct evidence is lacking. In this study, we investigated the impact of unilateral nephrectomy on the dynamic changes in Aβ in the blood and brain in both humans and animals and on behavioural deficits and AD pathologies in animals. Furthermore, the therapeutic effects of the diuretic furosemide on Aβ clearance via the kidney were assessed. We detected Aβ in the kidneys and urine of both humans and animals and found that the Aβ level in the blood of the renal artery was higher than that in the blood of the renal vein. Unilateral nephrectomy increased brain Aβ deposition; aggravated AD pathologies, including Tau hyperphosphorylation, glial activation, neuroinflammation, and neuronal loss; and aggravated cognitive deficits in APP/PS1 mice. In addition, chronic furosemide treatment reduced blood and brain Aβ levels and attenuated AD pathologies and cognitive deficits in APP/PS1 mice. Our findings demonstrate that the kidney physiologically clears Aβ from the blood, suggesting that facilitation of Aβ clearance via the kidney represents a novel potential therapeutic approach for AD.

Placenta accreta spectrum disorder (PASD) and placenta previa (PP) are two of the most hideous obstetric complications which are usually associated with a history of cesarean section (CS). Moreover, women with PASD, PP and/or a cesarean scarred uterus are more likely to have adverse pregnancy outcomes, including blood transfusion, hysterectomy, pelvic organs damage, postpartum hemorrhage, disseminated intravascular coagulation, multi-organ dysfunction syndrome and even maternal or fetal death. This study aimed to investigate the efficacy of precesarean internal iliac artery balloon catheterization (BC) for managing severe hemorrhage caused by PASD and PP with a history of CS. This participant-assigned interventional study was conducted in Tongji Hospital. We recruited 128 women with suspected PASD, PP and a history of CS. Women in the BC group accepted precesarean BC of bilateral internal iliac arteries before the scheduled cesarean delivery. Women in the control group underwent a conventional cesarean delivery. Intraoperative hemorrhage, transfusion volume, radiation dose, exposure time, complications and neonatal outcomes were discussed. There were significant differences in calculated blood loss (CBL) between BC group and control group (1015.0±144.9 vs. 1467.0±171.0 mL, P=0.04). Precesarean BC could reduce intraoperative red blood cell (RBC) transfusion as compared with control group (799.5±136.1 vs. 1286.0±161.6 mL, P=0.02) and lessen the rate of using blood products (57.1% vs. 76.4%, P=0.02). The incidence of hysterectomy was also lower in BC group than in control group. Postpartum outcomes showed no significant differences between the two groups, except that postoperation hospitalization was longer in BC group than in control group (6.7±0.4 vs. 5.8±0.2 days, P=0.03). Precesarean BC of internal iliac artery is an effective method for managing severe hemorrhage caused by PASD and PP with a cesarean scarred uterus, as it could reduce intraoperative blood loss, lessen intraoperative RBC transfusions and potentially decrease hysterectomies.

Object detection is an essential technology in the computer vision domain and plays a vital role in intelligent transportation. Intelligent vehicles utilize object detection on images for environment perception. This work develops a target detection algorithm based on deep learning technologies, particularly convolutional neural networks and neural network modeling. Building on the analysis of the traditional Haar-like vehicle recognition algorithm, a vehicle recognition algorithm based on a convolutional neural network with fused edge features (FE-CNN) is proposed. The experimental results demonstrate that FE-CNN improves the recognition precision and the model’s convergence speed through a simple and effective edge feature fusion method. In the experiment conducted using real traffic scene for vehicle recognition, the developed algorithm achieves a 99.82% recognition rate in efficient time, demonstrating the capability for real-time performance and accurate target detection.

Spatial position consistency and occlusion consistency are two important problems in augmented reality systems. In this paper, we proposed a novel method that can address the registration problem and occlusion problem simultaneously by using an RGB-D camera. First, to solve the image alignment errors caused by the imaging mode of the RGB-D camera, we developed a depth map inpainting method that combines the FMM and RGB-D information. Second, we established an automatic method to judge the close-range mode based on the depth histogram to solve the registration failure problem caused by hardware limitations. In the close-range mode, the registration method combining the fast ICP and ORB was adopted to calculate the camera pose. Third, we developed an occlusion handling method based on the geometric analysis of the scene. Several experiments were performed to validate the performance of the proposed method. The experimental results indicate that our method can obtain stable and accurate registration and occlusion handling results in both the close-range and non-close-range modes. Moreover, the mutual occlusion problem can be handled effectively, and the proposed method can satisfy the real-time requirements of augmented reality systems.

A two-phase closed thermosyphon (TPCT) with a CuO–H2O nanofluid was used to effectively harness the internal accumulation of thermal energy from a coal pile, formerly subject to the risk of spontaneous combustion. The heat transfer effect of different insertion ratios of the TPCT (evaporation section:condensation section = 1:3, 1:2, and 2:3) and inclination angles (30°, 45°, 60°, and 90°) was investigated for bituminous coal. The results indicated that the heat transfer effect of the insertion ratio, in descending order of preference, was 2:3 > 1:2 > 1:3. When the TPCT insertion ratio was 2:3, the maximum temperature difference was up to 37.7 °C. The heat transfer effects of the TPCT were strengthened when it was inserted at a given angle. In decreasing order of effectiveness, the tested inclination angles showed the following order of preference: 60° > 30° > 45° > 90°. Therefore, 60° was the optimal insertion angle. In general, TPCT has the optimal transfer effects when the insertion ratio is 2:3 and the inclination angle is 60°.

As a two-dimensional semiconductor with many physical properties, including, notably, layer-controlled electronic bandgap and coupled spin-valley degree of freedom, monolayer MoSe2 is a strong candidate material for next-generation opto- and valley-electronic devices. However, due to substrate effects such as lattice mismatch and dielectric screening, preserving the monolayer's intrinsic properties remains challenging. This issue is generally significant for metallic substrates whose active surfaces are commonly utilized to achieve direct chemical or physical vapor growth of the monolayer films. Here, we demonstrate high-temperature-annealed Au foil with well-defined (100) facets as a weakly interacting substrate for atmospheric pressure chemical vapor deposition of highly crystalline monolayer MoSe2. Low-temperature scanning tunneling microscopy/spectroscopy measurements reveal a honeycomb structure of MoSe2 with a quasi-particle bandgap of 1.96 eV, a value comparable with other weakly interacting systems such as MoSe2/graphite. Density functional theory calculations indicate that the Au(100) surface exhibits the preferred energetics to electronically decouple from MoSe2, compared with the (110) and (111) crystal planes. This weak coupling is critical for the easy transfer of monolayers to another host substrate. Our study demonstrates a practical means to produce high-quality monolayers of transition-metal dichalcogenides, viable for both fundamental and application studies.

Throughout the past 2020, the pandemic COVID-19 has caused a big global shock, meanwhile it brought a great impact on the public health network. Trauma emergency system faced a giant challenge and how to manage trauma under the pandemic of COVID-19 was widely discussed. However, the trauma treatment of special population (geriatric patients and patients taking anticoagulant drugs) has received inadequate attention. Due to the high mortality following severe traumatic hemorrhage, hemostasis and trauma-induced coagulopathy are the important concerns in trauma treatment. Sepsis is another topic should not be ignored when we talking about trauma. COVID-19 itself is a special kind of sepsis, and it may even be called as serious systemic infection syndrome. Sepsis has been become a serious problem waiting to be solved urgently no matter in the fields of trauma, or in intensive care and infection, etc. This article reviewed the research progress in areas including trauma emergency care, trauma bleeding and coagulation, geriatric trauma and basic research of trauma within 2020.

The aim of this study was to investigate the efficacy and safety of initial Gamma Knife radiosurgery (GKRS) for elderly patients with nonfunctioning pituitary adenomas (NFPAs). We retrospectively reviewed 45 elderly patients underwent GKRS as the initial treatment for NFPAs at our institution between December 2007 and December 2017. Patients’ radiographic and clinical data were collected. The median age of patients at the time of GKRS was 71 years (range 65–82 years). The median tumor volume was 2.6 cm3 (range 0.3–21.8 cm3). The median marginal dose was 13 Gy (range 6–23 Gy). The median maximum dose to the optic apparatus was 6.5 Gy (range 2.3–10.3 Gy). Thirty-five patients (77.8%) achieved tumor regression, 6 patients (13.3%) had tumor stable and 4 patients (8.9%) occurred tumor progression during a median radiological follow-up time of 51.4 months (range 11.1–158.7 months). The crude tumor control rate was 91.1%. The actuarial tumor control rates were 100%, 95.0%, 87.6%, and 87.6%, at 1, 3, 5, and 10 years after initial GKRS, respectively. New-onset hypopituitarism occurred in 6 patients. Two patients with pre-GKRS visual dysfunction developed further deterioration of visual function. No other radiation-induced complications were noted. Initial GKRS can provide a high tumor control rate as well as low risk of postradiosurgical complications for elderly patients with NFPAs. Attention should be paid to avoid radiation-related adverse effects including hypopituitarism, optic neuropathy and cranial neuropathy in elderly patients.

BACKGROUND Adenosquamous carcinoma (ASC), which is comprised of squamous cell carcinoma (SCC) and adenocarcinoma elements, is a rare histological type of esophageal carcinoma. Few reports have focused on the endoscopic findings and the effectiveness of the endoscopic treatment of early ASC. CASE SUMMARY A 77-year-old man underwent esophagogastroduodenoscopy for heartburn. A flat lesion with an uneven and slightly elevated central portion was found in the distal esophagus. Magnifying endoscopy with narrow-band imaging showed a well-demarcated brownish area with dendritically branched abnormal vessels and highly irregular intrapapillary capillary loops. A histopathological diagnosis of SCC was obtained by endoscopic biopsy. Endoscopic ultrasonography revealed a hypoechoic mass confined to the mucosa layer. The lesion was suspected to be SCC with invasion into the muscularis mucosa. The lesion was resected en bloc by endoscopic submucosal dissection and histologically diagnosed as esophageal ASC limited within the muscularis mucosa, which was completely resected without lymphovascular or neural invasion. The SCC element was the pre-dominant element. The adenocarcinoma element formed ductal and nested structures distributed in a focal pattern. The patient underwent only endoscopic submucosal dissection and has been under annual endoscopic and radiographic surveillance for 3 years without recurrence. CONCLUSION For early ASC confined within the mucosal layer, complete endoscopic resection might also be a curative treatment.

Purpose: MET tyrosine kinase inhibitors (TKIs) can achieve modest clinical outcomes in MET exon 14–altered lung cancers, likely secondary to primary resistance. Mechanisms of primary resistance remain poorly characterized and comprehensive proteomic analyses have not previously been performed. Experimental Design: We performed hybrid capture-based DNA sequencing, targeted RNA sequencing, cell-free DNA sequencing, selected reaction monitoring mass spectrometry (SRM-MS), and immunohistochemistry on patient samples of MET exon 14–altered lung cancers treated with a MET TKI. Associations between overall response rate (ORR), progression-free survival (PFS), and putative genomic alterations and MET protein expression were evaluated. Results: Seventy-five of 168 MET exon 14–altered lung cancers received a MET TKI. Previously undescribed (zygosity, clonality, whole-genome duplication) and known (copy-number focality, tumor mutational burden, mutation region/type) genomic factors were not associated with ORR/PFS (P > 0.05). In contrast, MET expression was associated with MET TKI benefit. Only cases with detectable MET expression by SRM-MS (N = 15) or immunochemistry (N = 22) responded to MET TKI therapy, and cancers with H-score ≥ 200 had a higher PFS than cancers below this cutoff (10.4 vs. 5.5 months, respectively; HR, 3.87; P = 0.02). Conclusions: In MET exon 14–altered cancers treated with a MET TKI, a comprehensive analysis of previously unknown and known genomic factors did not identify a genomic mechanism of primary resistance. Instead, MET expression correlated with benefit, suggesting the potential role of interrogating the proteome in addition to the genome in confirmatory prospective trials.

Blockchain technology has a tendency to make revolutionary changes for all walks of life with its public, distributed, decentration and unforgeable characteristics. However, with the rapid development of the quantum computer, many extant cryptographic algorithms applied in blockchain-enabled systems are vulnerable to the quantum attacks. In this paper, an anti-quantum blind signature scheme based on the lattice assumption has been proposed. As lattice cryptography is the main candidate algorithm in post-quantum cryptosystems and the blind signature scheme is widely used in e-cash and voting for creating untraceable payment system, which are more suitable for privacy preserving in blockchain-enabled systems. In the proposed scheme, the bimodal Gaussian distribution, Reject sampling and other technologies have been used to improve the security and efficiency. Then, the proposed blind signature can satisfy the properties of blindness and one-more unforgeability, and it also can prove to be safe in the random oracle model. Moreover, the efficiency analysis and comparison results show that the proposed scheme is more efficient than the similar literatures and has a more stabilized signature size than other cryptosystems.

Papillary meningioma (PM) is a rare central nervous system tumor. We aimed to analyze the characteristics and outcomes of patients with PM (WHO grade III) and identify risk factors that influence survival using the Surveillance, Epidemiology, and End Results (SEER) database. Clinical characteristics, tumor features, and outcomes of 108 PM patients included in the SEER database between 1990 and 2016 were retrieved. Risk factors related to prognosis of PM were assessed by Kaplan–Meier curves and the Cox proportional hazards model. All 108 patients, including 65 males and 43 females (1.5:1), with a median age of 52 years (range, 9 to > 85 years) had undergone surgical resection. Gross total resection (GTR) was achieved in 50%, and 50% underwent subtotal resection (STR). While 55.6% underwent postoperative radiation therapy, 48% did not. The median disease-specific survival (DSS) was 128 months, and the 5-year DSS rate was 77%. In multivariate analysis, age ≤ 52 years and GTR were both independently associated with higher probability of DSS (p = 0.033 and p = 0.029, respectively). Stratification analysis showed that postoperative radiotherapy had no significant impact on the DSS, irrespective of resection extent (p = 0.172). Our SEER analysis showed that age and extent of resection were prognostic factors for PM, but race, tumor size, gender, chemotherapy, and postoperative radiotherapy did not significantly impact DSS of PM patients. There was no significant improvement in survival of patients who underwent radiotherapy and GTR, or radiotherapy and STR, compared with GTR or STR alone.

Valvular heart disease is an important disease that endangers human health and heart valve replacement has become one of the main treatments for patients with severe valvular heart disease. However, the traditional surgical valve replacement (SVR) suffers several drawbacks such as high risk, great trauma and long recovery time, and more than 30% of patients are intolerant to SVR, especially elderly patients. In recent years, with the development of minimally invasive technology, transcatheter heart valve replacement (THVR) as a method of implantation without thoracotomy has become an optimal treatment for severe valvular heart disease due to its advantages of minimal trauma, low risk and fast recovery. Meanwhile, the usage of bioprosthetic heart valves (BHVs) has been enlarged greatly with the rapid development of THVR and the aging population. Most BHVs in clinics are crosslinked by glutaraldehyde (Glut), which shows great mechanical properties and chemical stability. However, some problems such as poor biocompatibility, calcification, coagulation and endothelialization difficulty also need to be solved urgently for Glut-treated BHVs. In this work, a non-Glut treated BHV from 7a-ethyltetrahydro-oxazolo[3,4-c]oxazole (OX-Et) crosslinked porcine pericardium (PP) has been developed. Compared with glutaraldehyde-crosslinked porcine pericardium (Glut-PP), good physical and chemical properties similar to Glut-PP are shown for OX-Et treated porcine pericardium (OX-Et-PP). It is noteworthy that better biocompatibility, endothelialization performance, and anti-coagulant effect as well as the improved anti-calcification property can also be observed for OX-Et-PP in the in vitro and in vivo study, potentially making OX-Et-PP a good candidate in the application of BHVs.

Background:. Recent studies suggest that a healthy diet helps to prevent the development of Alzheimer disease (AD). This study aimed to investigate whether spicy food consumption is associated with cognition and cerebrospinal fluid (CSF) biomarkers of AD in the Chinese population. Methods:. We enrolled 55 AD patients and 55 age- and gender-matched cognitively normal (CN) subjects in a case-control study, as well as a cohort of 131 participants without subjective cognitive decline (non-AD) in a cross-sectional study. Spicy food consumption was assessed using the Food Frequency Questionnaire (FFQ). Associations of FFQ scores with cognition and CSF biomarkers of AD were analyzed. Results:. In the case-control study, spicy food consumption was lower in AD patients than that in CNs (4.0 [4.0–8.0] vs. 8.0 [4.5–10.0], P

Many real-world problems can be abstracted into graph classification problems. Recently, graph convolutional networks have achieved great success in the task of node classification and link prediction. However, when using graph convolution network to process the task of graph classification, either global topology information or local information is ignored. Therefore, designing graph convolutional networks to improve the accuracy of graph classification has attracted more and more attention. Inspired by the use of convolutional neural networks to process graph-structured data, we put forward a new spatial convolutional neural network architecture for graph classification. To be specific, we first design a comprehensive weighting method to measure the significance of vertices in the graph based on multiple indicators to choose the central node sequence. Then, the normalization process of the graph is realized by constructing the same size neighborhood graphs for the central vertices. After that, the structural characteristics of the graph are extracted from both local and global aspects. Finally, the tensors obtained after the above steps are respectively input into the following two spatial convolutional neural network architectures to perform classification, one is a simple CNN structure, which has only two convolution layers, one dense layer and one softmax layer. The other is to modify the architecture of CNN, and the channel concatenation layer is introduced to determine the classification result of the entire graph according to the category of the neighborhood graphs. Experimental results on two kinds of real-world datasets, bioinformatics and social network datasets, indicate that our approach obtains competitive results and is superior to some classic kernels and similar deep learning-based algorithms on 6 out of 8 benchmark data sets.

The anonymity of the Internet used to be considered as an encouraging factor that helped learners engage in online learning. However, academic studies on anonymity have found that its effect on learning is context-dependent or mixed. In this research, we focused on massive open online course (MOOC) learners’ preference for personal name disclosure in their screen names as a predictor of their final achievement levels (FALs) at the end of a course including 2606 active learners. We conducted two studies, one to examine the associations between these two variables and one to demonstrate how such associations can be utilized in MOOC FAL prediction. We found that MOOC learners who included personal names in their MOOC screen names significantly outperformed other learners in their FALs (p < 0.001). We also found that screen name preference improved FAL prediction accuracy utilizing natural language processing and proper machine learning technologies. The error rate was reduced to 4.03% by a random forest algorithm with an appropriate feature combination: the personal name disclosure indicator (PNDI), quiz scores, number of replies, and exam scores. The results are potentially useful for the development of an early intervention to provide different types of help to students who prefer to disclose personal names and those who do not. The practical effects of these interventions will be examined in the future. In addition, whether the course difficulty level or course type affects the associations between personal name disclosure and FAL will also be examined.

Conversation generation is an important natural language processing task and has attracted much attention in recent years. The realization of the conversation model is also of great significance to the field of social computing, helping to build artificial intelligence robots on social networks. The open domain conversation model is fundamentally data-driven, which can be roughly divided into retrieval models and generation models. Although remarkable progress has been achieved in recent years, it is still difficult to get responses that are grammatically and semantically appropriate. We propose the Rerank of Retrieval-based and Transformer-based Conversation model (RRT), a novel conversation model that combines the retrieval model with the generation model for the purpose of obtaining context–appropriate response. The context–response pairs with the highest similarity from training set are retrieved using traditional retrieval method, and further ranked to obtain the retrieval candidate response. We replaced the traditional sequence-to-sequence models for conversation generation by the transformer model and achieved better results with less training time. Finally, the post-reranking module is used to rank the retrieved candidate and the generated one to obtain the final response. We conducted detailed experiments on two datasets and the results show that compared with the traditional generation model, our model has a significant improvement in each metric, and the training time is decreased by a factor of 5. Furthermore, our model is more informative and relevant to the input context than the retrieval model.

Introduction: Gamma Knife radiosurgery (GKRS) has been used to treat cavernous malformations (CMs) located in basal ganglia and thalamus. However, previous reports are limited by small patient population. Methods: We retrospectively reviewed the clinical and radiological data of 53 patients with CMs of basal ganglia and thalamus who underwent GKRS at West China Hospital between May 2009 and July 2018. All patients suffered at least once bleeding before GKRS. The mean volume of these lesions was 1.77 cm3, and the mean marginal dose was 13.2 Gy. After treatment, patients were followed to determine the change in symptom and hemorrhage event. Results: The mean follow-up period was 52.1 months (6.2–104.3 months). The calculated annual hemorrhage rate (AHR) was 48.5% prior to GKRS and 3.0% after treatment (p < 0.001). The Kaplan-Meier analysis revealed that 2-, 3-, and 5-year hemorrhage-free survival were 88, 80.9, and 80.9%, respectively. Preexisting symptoms were resolved in 11 patients, improved in 14, and stable in 5. Only 2 patients (3.8%) developed new neurological deficit. Conclusion: Our study suggests that AHR after GKRS was comparable to the recorded AHR of natural history (3.1–4.1%) in previous studies. GKRS is a safe and effective treatment modality for CMs of basal ganglia and thalamus. Considering the relative insufficient understanding of natural history of CMs, future study warrants longer follow-up.

With the fast proliferation of device sensing and computing, crowed sensing has become the building block of the Internet of things. Consequently, various data collection and incentive mechanisms are investigated for people-centric services. In this paper, we have investigated the problem of privacy-aware people-centric IoT service based on a tailored auction approach. We applied a bi-tier differential privacy methodology on the data collected from crowdsensing IoT devices. A corresponding pricing scheme is also proposed to ensure the property of incentive compatibility, precise service data, and anonymized query results. Comparing to traditional privacy-aware auction schemes which only focus on the cost, our corresponding precise privacy-aware auction scheme provides a tailored IoT service based on the customers’ request. The proposed trial query technique is able to provide a precise assessment of service quality, thus improves the efficiency of the people-centric IoT service. The customer could enjoy the convenience of service evaluation before making a bid, while the actual service data is anonymized to guarantee the service providers’ interests. We evaluate the proposed bi-tier differential privacy schema for auction-based service by conducting extensive simulations. The experimental results show that our proposed method yields higher data utility and accuracy for the IoT service customers with privacy concerns.

Objective: To explore the effect of Sirt1 on the function of endothelial progenitor cells (EPCs) in rats with chronic obstructive pulmonary disease (COPD). Methods: A rat COPD model was established via smoking and endotoxin administration for three months. The peripheral circulating EPCs were isolated by gradient centrifugation, and their functions, cell cycle distribution, apoptosis, and Sirt1 expression were examined. The function changes of EPCs in the presence or absence of Sirt1 agonist and inhibitor were estimated; meanwhile, the expressions of Sirt1, FOXO3a, NF-κB, and p53 were also evaluated. Results: The proliferation, adhesion, and migration of EPCs decreased while the apoptosis rate was increased in the COPD rats. The expression of Sirt1 protein in EPCs of the COPD group was significantly lower than that in the control group (P

With the fast development of various computing paradigms, the amount of data is rapidly increasing that brings the huge storage overhead. However, the existing data deduplication techniques do not ...

Healthcare applications on Voice Personal Assistant System (e.g., Amazon Alexa), have shown a great promise to deliver personalized health services via a conversational interface. However, concerns are also raised about privacy, safety, and service quality. In this paper, we propose VerHealth, to systematically assess health-related applications on Alexa for how well they comply with existing privacy and safety policies. VerHealth contains a static module and a dynamic module based on machine learning that can trigger and detect violation behaviors hidden deep in the interaction threads. We use VerHealth to analyze 813 health-related applications on Alexa by sending over 855,000 probing questions and analyzing 863,000 responses. We also consult with three medical school students (domain experts) to confirm and assess the potential violations. We show that violations are quite common, e.g., 86.36% of them miss disclaimers when providing medical information; 30.23% of them store user physical or mental health data without approval. Domain experts believe that the applications' medical suggestions are often factually-correct but are of poor relevance, and applications should have asked more questions before providing suggestions for over half of the cases. Finally, we use our results to discuss possible directions for improvements.

In this paper, we propose a new method for hyperspectral images (HSI) classification, aiming to take advantage of both manifold learning-based feature extraction and neural networks by stacking layers applying locality sensitive discriminant analysis (LSDA) to broad learning system (BLS). BLS has been proven to be a successful model for various machine learning tasks due to its high feature representative capacity introduced by numerous randomly mapped features. However, it also produces redundancy, which is indiscriminate and finally lowers its performance and causes heavy computing demand, especially in cases of the input data bearing high dimensionality. In our work, a manifold learning method is integrated into the BLS by inserting two LSDA layers before the input layer and output layer separate, so the spectral-spatial HSI features are fully utilized to acquire the state-of-the-art classification accuracy. The extensive experiments have shown our method’s superiority.

Deficits in the clearance of amyloid β-protein (Aβ) play a pivotal role in the pathogenesis of sporadic Alzheimer’s disease (AD). The roles of blood monocytes in the development of AD remain unclear. In this study, we sought to investigate the alterations in the Aβ phagocytosis function of peripheral monocytes during ageing and in AD patients. A total of 104 cognitively normal participants aged 22–89 years, 24 AD patients, 25 age- and sex-matched cognitively normal (CN) subjects, 15 Parkinson’s disease patients (PD), and 15 age- and sex-matched CN subjects were recruited. The Aβ uptake by blood monocytes was measured and its alteration during ageing and in AD patients were investigated. Aβ1-42 uptake by monocytes decreased during ageing and further decreased in AD but not in PD patients. Aβ1-42 uptake by monocytes was associated with Aβ1-42 levels in the blood. Among the Aβ uptake-related receptors and enzymes, the expression of Toll-like receptor 2 (TLR2) was reduced in monocytes from AD patients. Our findings suggest that monocytes regulate the blood levels of Aβ and might be involved in the development of AD. The recovery of the Aβ uptake function by blood monocytes represents a potential therapeutic strategy for AD.