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Abnormal gray matter (GM) asymmetry has been verified in autism spectrum disorder (ASD), which is characterized by high heterogeneity. ASD is distinguished by three core symptom domains. Previous neuroimaging studies have offered support for divergent neural substrates of different core symptom domains in ASD. However, no previous study has explored GM asymmetry alterations underlying different core symptom domains. This study sought to clarify atypical GM asymmetry patterns underlying three core symptom domains in ASD with a large sample of 230 minors with ASD (ages 7–18 years) and 274 matched TD controls from the Autism Brain Imaging Data Exchange I (ABIDE I) repository. To this end, the scores of the revised autism diagnostic interview (ADI-R) subscales were normalized for grouping ASD into three core-symptom-defined subgroups: social interaction (SI), verbal communication (VA), and restricted repetitive behaviors (RRB). We investigated core-symptom-related GM asymmetry alterations in ASD resulting from advanced voxel-based morphometry (VBM) by general linear models. We also examined the relationship between GM asymmetry and age and between GM asymmetry and symptom severity assessed by the Autism Diagnostic Observation Schedule (ADOS). We found unique GM asymmetry alterations underlying three core-symptom-defined subgroups in ASD: more rightward asymmetry in the thalamus for SI, less rightward asymmetry in the superior temporal gyrus, anterior cingulate and caudate for VA, and less rightward asymmetry in the middle and inferior frontal gyrus for RRB. Furthermore, the asymmetry indexes in the thalamus were negatively associated with ADOS_SOCIAL scores in the general ASD group. We also showed significant correlations between GM asymmetry and age in ASD and TD individuals. Our results support the theory that each core symptom domain of ASD may have independent etiological and neurobiological underpinnings, which is essential for the interpretation of heterogeneity and the future diagnosis and treatment of ASD.

BackgroundEarly identification of synchronous distant metastasis (SDM) in patients with clear cell Renal cell carcinoma (ccRCC) can certify the reasonable diagnostic examinations.MethodsThis retrospective study recruited 463 ccRCC patients who were divided into two cohorts (training and internal validation) at a 7:3 ratio. Besides, 115 patients from other hospital were assigned external validation cohort. A radiomics signature was developed based on features by means of the least absolute shrinkage and selection operator method. Demographics, laboratory variables and CT findings were combined to develop clinical factors model. Integrating radiomics signature and clinical factors model, a radiomics nomogram was developed.ResultsTen features were used to build radiomics signature, which yielded an area under the curve (AUC) 0.882 in the external validation cohort. By incorporating the clinical independent predictors, the clinical model was developed with AUC of 0.920 in the external validation cohort. Radiomics nomogram (external validation, 0.925) had better performance than clinical factors model or radiomics signature. Decision curve analysis demonstrated the superiority of the radiomics nomogram in terms of clinical usefulness.ConclusionsThe CT-based nomogram could help in predicting SDM status in patients with ccRCC, which might provide assistance for clinicians in making diagnostic examinations.

Abstract Background Knowledge on the pharmacodynamic effects of antiplatelet drugs including clopidogrel and ticagrelor on Asian patients is scarce. We aim to evaluate the effects of the two drugs on platelet reactivity in the treatment of Chinese patients who underwent percutaneous coronary intervention (PCI), using two platelet function tests (PFT). Meanwhile, the relationship between mean platelet volume (MPV), a routine index of platelet size, and high on-treatment platelet reactivity (HPR) is also investigated. Methods Patients receiving dual antiplatelet therapy (DAPT) were scheduled for the assessment of platelet reactivity at 2–3 days after PCI. Two PFTs, light transmission aggregometry (LTA) and vasodilator-stimulated phosphoprotein (VASP)-FCM assay, were applied in the evaluation of platelet reactivity. The MPV was measured simultaneously with EDTA plasma using a Sysmex XN 2000 automated hematology analyzer. Results The final study population included the aspirin + clopidogrel group (n = 46) and the aspirin + ticagrelor group (n = 66). In the aspirin + ticagrelor group, the maximal light transmittance (LT) changes in response to 5 μM ADP assessed by LTA was obviously lower than that in the aspirin + clopidogrel group (P

Abstract Objective This study was aimed to evaluate the effect of preoperative composite inflammatory index on adhesional perinephric fat (APF), providing a help for preoperative risk assessment of laparoscopic partial nephrectomy (LPN) in patients with renal cell carcinoma. Materials and methods A retrospective study was conducted on 231 patients with renal cell carcinoma, who underwent laparoscopic partial nephrectomy. They were divided into two groups according to whether there was APF during operation. Relevant clinical data, laboratory parameters and imaging examination were obtained before operation to calculate the composite inflammatory index and MAP score. The composite inflammatory index was divided into high value group and low value group by ROC curve method. The related predictive factors of APF were analyzed by logistic regression method. Results The APF was found in 105 patients (45.5%). In multivariate analysis, systemic immune inflammation index (SII) (high/low), MAP score, tumor size and perirenal fat thickness were independent predictors of APF. The operation time of patients with APF was longer, and the difference of blood loss was not statistically significant. Conclusion SII is an independent predictor of APF before laparoscopic partial nephrectomy. Trial registration ChiCTR, ChiCTR2100045944. Registered 30 April 2021—Retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=125703 .

Objective: No new U-net (nnU-Net) is a newly-developed deep learning neural network, whose advantages in medical image segmentation have been noticed recently. This study aimed to investigate the value of the nnU-Net-based model for computed tomography angiography (CTA) imaging in assisting the evaluation of carotid artery stenosis (CAS) and atherosclerotic plaque.Methods: This study retrospectively enrolled 93 CAS-suspected patients who underwent head and neck CTA examination, then randomly divided them into the training set (N = 70) and the validation set (N = 23) in a 3:1 ratio. The radiologist-marked images in the training set were used for the development of the nnU-Net model, which was subsequently tested in the validation set.Results: In the training set, the nnU-Net had already displayed a good performance for CAS diagnosis and atherosclerotic plaque segmentation. Then, its utility was further confirmed in the validation set: the Dice similarity coefficient value of the nnU-Net model in segmenting background, blood vessels, calcification plaques, and dark spots reached 0.975, 0.974 0.795, and 0.498, accordingly. Besides, the nnU-Net model displayed a good consistency with physicians in assessing CAS (Kappa = 0.893), stenosis degree (Kappa = 0.930), the number of calcification plaque (Kappa = 0.922), non-calcification (Kappa = 0.768) and mixed plaque (Kappa = 0.793), as well as the max thickness of calcification plaque (intraclass correlation coefficient = 0.972). Additionally, the evaluation time of the nnU-Net model was shortened compared with the physicians (27.3 ± 4.4 s vs. 296.8 ± 81.1 s, p < 0.001).Conclusion: The automatic segmentation model based on nnU-Net shows good accuracy, reliability, and efficiency in assisting CTA to evaluate CAS and carotid atherosclerotic plaques.

Abstract Background Fluorescence imaging as the beacon for optical navigation has wildly developed in preclinical studies due to its prominent advantages, including noninvasiveness and superior temporal resolution. However, the traditional optical methods based on ultraviolet (UV, 200–400 nm) and visible light (Vis, 400–650 nm) limited by their low penetration, signal-to-noise ratio, and high background auto-fluorescence interference. Therefore, the development of near-infrared-II (NIR-II 1000–1700 nm) nanoprobe attracted significant attentions toward in vivo imaging. Regrettably, most of the NIR-II fluorescence probes, especially for inorganic NPs, were hardly excreted from the reticuloendothelial system (RES), yielding the anonymous long-term circulatory safety issue. Results Here, we develop a facile strategy for the fabrication of Nd3+-doped rare-earth core–shell nanoparticles (Nd-RENPs), NaGdF4:5%Nd@NaLuF4, with strong emission in the NIR-II window. What’s more, the Nd-RENPs could be quickly eliminated from the hepatobiliary pathway, reducing the potential risk with the long-term retention in the RES. Further, the Nd-RENPs are successfully utilized for NIR-II in vivo imaging and magnetic resonance imaging (MRI) contrast agents, enabling the precise detection of breast cancer. Conclusions The rationally designed Nd-RENPs nanoprobes manifest rapid-clearance property revealing the potential application toward the noninvasive preoperative imaging of tumor lesions and real-time intra-operative supervision. Graphical abstract

Abstract This paper investigates the joint relay and channel selection problem using a deep reinforcement learning (DRL) algorithm for cooperative communications in a dynamic jamming environment. The latest types of jammers include the mobile and smart jammer that contains multiple jamming patterns. This new type of jammer poses serious challenges to reliable communications such as huge environment states, tightly coupled joint action selections and real‐time decision requirements. To cope with these challenges, a DRL‐based relay‐assisted cooperative communication scheme is proposed. In this scheme, the joint selection problem is constructed as a Markov decision process (MDP) and a double deep Q network (DDQN) based anti‐jamming scheme is proposed to address the unknown and dynamic jamming behaviors. Concretely, a joint decision‐making network composed of three sub‐networks is designed and the independent learning method of each sub‐network is proposed. The simulation results show that the user agent is able to anticipate the jammer behaviors and elude the jamming in advance. Furthermore, compared with the sensing‐based algorithm, the Q learning‐based algorithm and the existing DRL‐based anti‐jamming approaches, the proposed algorithm maintains a higher average normalized throughput.

Background: The coronavirus disease-2019 (COVID-19) pandemic significantly affected management of cardiovascular disease around the world. The effect of the pandemic on volume of cardiovascular diagnostic procedures is not known. Objectives: This study sought to evaluate the effects of the early phase of the COVID-19 pandemic on cardiovascular diagnostic procedures and safety practices in Asia. Methods: The International Atomic Energy Agency conducted a worldwide survey to assess changes in cardiovascular procedure volume and safety practices caused by COVID-19. Testing volumes were reported for March 2020 and April 2020 and were compared to those from March 2019. Data from 180 centers across 33 Asian countries were grouped into 4 subregions for comparison. Results: Procedure volumes decreased by 47% from March 2019 to March 2020, showing recovery from March 2020 to April 2020 in Eastern Asia, particularly in China. The majority of centers cancelled outpatient activities and increased time per study. Practice changes included implementing physical distancing and restricting visitors. Although COVID testing was not commonly performed, it was conducted in one-third of facilities in Eastern Asia. The most severe reductions in procedure volumes were observed in lower-income countries, where volumes decreased 81% from March 2019 to April 2020. Conclusions: The COVID-19 pandemic in Asia caused significant reductions in cardiovascular diagnostic procedures, particularly in low-income countries. Further studies on effects of COVID-19 on cardiovascular outcomes and changes in care delivery are warranted.

Energy problems have become increasingly prominent. The use of thermal insulation materials is an effective measure to save energy. As an efficient energy-saving material, nanocellulose aerogels have broad application prospects. However, nanocellulose aerogels have problems such as poor mechanical properties, high flammability, and they easily absorbs water from the environment. These defects restrict their thermal insulation performance and severely limit their application. This review analyzes the thermal insulation mechanism of nanocellulose aerogels and summarizes the methods of preparing them from biomass raw materials. In addition, aiming at the inherent defects of nanocellulose aerogels, this review focuses on the methods used to improve their mechanical properties, flame retardancy, and hydrophobicity in order to prepare high-performance thermal insulation materials in line with the concept of sustainable development, thereby promoting energy conservation, rational use, and expanding the application of nanocellulose aerogels.

Free-space optical (FSO) communication is widely used in satellites, ships, aircraft, and ground stations due to its advantages of high speed, large capacity, good confidentiality, and strong anti-interference ability. Variable-beam divergence angle (VBDA) technology makes FSO systems more flexible; this has the benefits of higher acquisition probability, stronger tracking ability, wider communication link range, and lower energy consumption. In other words, the study of VBDA has both theoretical significance and practical relevance. This paper conducts a comprehensive search of relevant scientific databases, journals, conference proceedings, patents, and books to identify publications related to VBDA technology. We analyze these publications, classify and organize various VBDA techniques based on their respective methods. To the best of our knowledge, this is the first review of VBDA technology. In this paper, we first explain the basic principle of changing the beam divergence angle by employing the ABCD matrix, and further furnish a detailed overview of the methods used for VBDA along with their corresponding advantages and disadvantages. In addition, we provide a comprehensive summary of the research conducted using VBDA technology across different link types. Lastly, we identify the challenges and potential future research directions for VBDA technology.

Sigmoid sinus wall dehiscence (SSWD) is an important etiology of venous pulsatile tinnitus (VPT) and is treated by sigmoid sinus wall reconstruction (SSWR). This study aimed to investigate the therapeutic effects of the different degrees of SSWR and the prognostic effect in patients with VPT. Personalized models of three patients with SSWD (control), 3/4SSWD, 1/2SSWD, 1/4SSWD, and 0SSWD were reconstructed. A multiphysics interaction approach was applied to elucidate the biomechanical and acoustic changes. Results revealed that after SSWR, the average pressure of venous vessel on the SSWD region reduced by 33.70 ± 12.53%, 35.86 ± 12.39%, and 39.70 ± 12.45% (mean ± SD) in three patients with 3/4SSWD, 1/2SSWD, and 1/4SSWD. The maximum displacement of the SSWR region reduced by 25.91 ± 30.20%, 37.20 ± 31.47%, 52.60 ± 34.66%, and 79.35 ± 18.13% (mean ± SD) in three patients with 3/4SSWD, 1/2SSWD, 1/4SSWD, and 0SSWD, with a magnitude approximately 10−3 times that of the venous vessel in the SSWD region. The sound pressure level at the tympanum reduced by 23.72 ± 1.91%, 31.03 ± 14.40%, 45.62 ± 19.11%, and 128.46 ± 15.46% (mean ± SD). The SSWR region was still loaded with high stress in comparison to the surrounding region. The SSWR region of the temporal bone effectively shielded the high wall pressure and blocked the transmission of venous vessel vibration to the inner ear. Patients with inadequate SSWR still had residual VPT symptoms despite the remission of VPT symptoms. Complete SSWR could completely solve VPT issues. High-stress distribution of the SSWR region may be the cause of the recurrence of VPT symptoms.

Abstract Purpose To investigate the performance of magnetic resonance imaging (MRI)-based radiomics models for benign and malignant prostate lesion discrimination and extracapsular extension (ECE) and positive surgical margins (PSM) prediction. Methods and materials In total, 459 patients who underwent multiparametric MRI (mpMRI) before prostate biopsy were included. Radiomic features were extracted from both T2-weighted imaging (T2WI) and the apparent diffusion coefficient (ADC). Patients were divided into different training sets and testing sets for different targets according to a ratio of 7:3. Radiomics signatures were built using radiomic features on the training set, and integrated models were built by adding clinical characteristics. The areas under the receiver operating characteristic curves (AUCs) were calculated to assess the classification performance on the testing sets. Results The radiomics signatures for benign and malignant lesion discrimination achieved AUCs of 0.775 (T2WI), 0.863 (ADC) and 0.855 (ADC + T2WI). The corresponding integrated models improved the AUC to 0.851/0.912/0.905, respectively. The radiomics signatures for ECE achieved the highest AUC of 0.625 (ADC), and the corresponding integrated model achieved the highest AUC (0.728). The radiomics signatures for PSM prediction achieved AUCs of 0.614 (T2WI) and 0.733 (ADC). The corresponding integrated models reached AUCs of 0.680 and 0.766, respectively. Conclusions The MRI-based radiomics models, which took advantage of radiomic features on ADC and T2WI scans, showed good performance in discriminating benign and malignant prostate lesions and predicting ECE and PSM. Combining radiomics signatures and clinical factors enhanced the performance of the models, which may contribute to clinical diagnosis and treatment.

Abstract Background Nuclear protein Ki-67 indicates the status of cell proliferation and has been regarded as an attractive biomarker for the prognosis of HCC. The aim of this study is to investigate which radiomics model derived from different sequences and phases of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI was superior to predict Ki-67 expression in hepatocellular carcinoma (HCC), then further to validate the optimal model for preoperative prediction of Ki-67 expression in HCC. Methods This retrospective study included 151 (training cohort: n = 103; validation cohort: n = 48) pathologically confirmed HCC patients. Radiomics features were extracted from the artery phase (AP), portal venous phase (PVP), hepatobiliary phase (HBP), and T2-weighted (T2W) images. A logistic regression with the least absolute shrinkage and selection operator (LASSO) regularization was used to select features to build a radiomics score (Rad-score). A final combined model including the optimal Rad-score and clinical risk factors was established. Receiver operating characteristic (ROC) curve analysis, Delong test and calibration curve were used to assess the predictive performance of the combined model. Decision cure analysis (DCA) was used to evaluate the clinical utility. Results The AP radiomics model with higher decision curve indicating added more net benefit, gave a better predictive performance than the HBP and T2W radiomic models. The combined model (AUC = 0.922 vs. 0.863) including AP Rad-score and serum AFP levels improved the predictive performance more than the AP radiomics model (AUC = 0.873 vs. 0.813) in the training and validation cohort. Calibration curve of the combined model showed a good agreement between the predicted and the actual probability. DCA of the validation cohort revealed that at a range threshold probability of 30–60%, the combined model added more net benefit compared with the AP radiomics model. Conclusions A combined model including AP Rad-score and serum AFP levels based on enhanced MRI can preoperatively predict Ki-67 expression in HCC.

PurposeThe aim of this study was to explore a new model of clinical decision-making to predict the occurrence of clinically significant prostate cancer (csPCa).Patients and MethodsThe demographic and clinical characteristics of 152 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), adjusted PSAD of peripheral zone (aPSADPZ), and peripheral zone volume ratio (PZ ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves.ResultsThe AUCs of PSA, PSAD, aPSADPZ, and PZ ratio were 0.521, 0.645, 0.745, and 0.717 for prostate cancer (PCa) diagnosis, while the corresponding values were 0.590, 0.678, 0.780, and 0.731 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of csPCa. The new model significantly improved the diagnostic accuracy of csPCa (0.865 vs. 0.741, p = 0.0284) compared with the base model. In addition, the new model was better than the base model for predicting csPCa in the low or medium probability while the number of patients with csPCa predicted by the new model was in good agreement with the actual number of patients with csPCa in the high-risk threshold.ConclusionsThis study demonstrates that aPSADPZ has a higher predictive accuracy for csPCa diagnosis than the conventional indicators. Including aPSADPZ, PZ ratio, and age can improve csPCa diagnosis and avoid unnecessary biopsies.

Background: Almost a year after the outbreak of coronavirus disease 2019 (COVID-19), many hospitalized COVID-19 patients have recovered. However, little is known about the long-term follow-up (> 2 months) of discharged patients. Methods: This study enrolled 527 discharged COVID-19 patients from 05 February to 11 March 2020. Basic characteristics, imaging features, nucleic acid detection results, and antibody levels of these patients were retrospectively reviewed. Results: Of the 527 discharged patients, 32 (6.1%) had re-detectable positive (RP) nucleic acid results for SARS-CoV-2 during follow-up examinations, with 11 and four detections entailing stool samples and anal swabs, respectively, rather than respiratory samples. Juveniles were more susceptible to “infection recurrence” than other age groups, with shorter time spans for re-detectable positive (RP) RNA tests (an average of 8.8 days [6.0–9.0 days]), while the reverse was true for the middle-aged group (17.5 days on average [14.0–17.5 days]). Similar improvements in the imaging features of both RP and no RP (NRP) groups were observed. Negative antibody detections in patients at 3 and 6 months after discharge were 14.2% and 25.0%, respectively. Cases evidencing negative antibodies were more common among juvenile patients (40% vs. 15.6%, P = 0.03) 6 months post-discharge. Conclusions: A total of 6.1% of 527 discharged patients showed RP status, which may be easier to be identified from stool samples than from other samples. Given the dropping rate of SARS-CoV-2 antibodies, reinfection may happen, especially in juvenile patients (aged

Background: The present exploration is aimed to determine whether diffusion kurtosis imaging (DKI)-derived mean diffusivity (MD) and mean kurtosis (MK) are possible parameters for the invasive breast cancer grading and whether MD/MK is related to breast cancer clinical-pathologic factors including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2) and Ki-67. Methods: Tumors from 108 invasive breast carcinoma patients (45.6 ± 11.2 years old; range, 20–84 years), diagnosed by pathological examination between January 2016 and August 2017, were included. DKI data (with b values of 0, 1000, 2000 sec/mm2) and MD/MK were measured. The expression of ER, PR, HER-2, and Ki-67 was evaluated by immunohistochemistry. Results: It was found that MD was significantly lower in grade III breast cancer than in grade II breast cancer (0.82 ± 0.21 vs 1.17 ± 0.24, p < 0.0001), while MK was significantly higher in grade III breast cancer than that in grade II breast cancer (1.00 ± 0.31 vs 0.85 ± 0.21, respectively; p < 0.05). In addition, MD was negatively associated with Ki-67 level (r = –0.39, p < 0.05), while MK was positively associated with Ki-67 level (r = 0.56, p < 0.05). Furthermore, MD was significantly increased in ER and PR positive expression group compared with ER and PR negative expression group, while there is no significant difference of MK in ER and PR positive expression group compared with ER and PR negative expression group. Additionally, there is no significant difference of MD and MK in HER-2 positive expression group compared with HER-2 negative expression group. Conclusions: These results demonstrate that DKI has value in the evaluation on the classification of invasive breast carcinoma. MD values were associated with breast cancer clinical-pathologic factors. DKI can provide useful information in the assessment of tumor proliferation activity.

The objective of this research is to explore the value of whole-thyroid CT-based radiomics in predicting benign (noncancerous) and malignant thyroid nodules. The imaging and clinical data of 161 patients with thyroid nodules that were confirmed by pathology were retrospectively analyzed. The entire thyroid regions of interest (ROIs) were manually sketched for all 161 cases. After extracting CT radiomic features, the patients were divided into a training group (128 cases) and a test group (33 cases) according to the 4:1 ratio with stratified random sampling (fivefold cross validation). All the data were normalized by the maximum absolute value and screened using selection operator regression analysis and K best. The data generation model was trained by logistic regression. The effectiveness of the model in differentiating between benign and malignant thyroid nodules was validated by a receiver operating characteristic (ROC) curve. After data grouping, eigenvalue screening, and data training, the logistic regression model with the maximum absolute value normalized was constructed. For the training group, the area under the ROC curve (AUC) was 94.4% (95% confidence interval: 0.941–0.977); the sensitivity and specificity were 89.7% and 86.7%, respectively; and the diagnostic accuracy was 87.6%. For the test group, the AUC was 94.2% (95% confidence interval: 0.881–0.999); the sensitivity and specificity were 89.4% and 86.8%, respectively; and the diagnostic accuracy was 87.6%. The CT radiomic model of the entire thyroid gland is highly efficient in differentiating between benign and malignant thyroid nodules.

A novel Mg(II) metal-organic framework (Mg-MOF) was synthesized based on the ligand of 2,2'-bipyridine-4,4'-dicarboxylic acid. Single-crystal X-ray structural analysis confirmed that three-dimensional-nanostructure Mg-MOFs formed a monoclinic system with a channel size of 15.733 Å × 23.736 Å. N2 adsorption isotherm, Fourier transform infrared spectroscopy, thermogravimetric analysis and high-resolution transmission electron microscopy were performed to characterize the thermal stability and purity of the Mg-MOFs. The adsorption studies on four typical volatile organic compounds (VOCs) emitted during wood drying showed that Mg-MOFs have noteworthy adsorption capacities, especially for benzene and β-pinene with adsorptions of 182.26 mg g−1 and 144.42 mg g−1, respectively. In addition, the adsorption of Mg-MOFs mainly occurred via natural adsorption, specifically, multi-layer physical adsorption, accompanied by chemical forces, which occurred in the pores where the VOCs molecules combined with active sites. As an adsorbent, Mg-MOFs exhibit versatile behaviour for toxic gas accumulation.

Abstract Background To develop and validate a nomogram for early identification of severe coronavirus disease 2019 (COVID-19) based on initial clinical and CT characteristics. Methods The initial clinical and CT imaging data of 217 patients with COVID-19 were analyzed retrospectively from January to March 2020. Two hundred seventeen patients with 146 mild cases and 71 severe cases were randomly divided into training and validation cohorts. Independent risk factors were selected to construct the nomogram for predicting severe COVID-19. Nomogram performance in terms of discrimination and calibration ability was evaluated using the area under the curve (AUC), calibration curve, decision curve, clinical impact curve and risk chart. Results In the training cohort, the severity score of lung in the severe group (7, interquartile range [IQR]:5–9) was significantly higher than that of the mild group (4, IQR,2–5) (P

Manual postprocessing of computed tomography angiography (CTA) images is extremely labor intensive and error prone. Here, the authors propose an artificial intelligence reconstruction system that can automatically achieve CTA reconstruction in healthcare services.

Abstract A study was carried out to investigate the release of volatile organic compounds (VOCs) during drying of plantation Pinus sylvestris grown in China and naturally grown Pinus sylvestris from Russia. Our purpose was to provide basic information that can help wood processing mills set their VOCs emission limits and control the exhaust gas within such limits. During conventional drying of the plantation Pinus sylvestris, a total of 22 chemical compounds were detected in the exhaust gas: 9 aldehydes including formaldehyde, 8 terpenes including α-pinene, and 3 additional compounds including alkane, and propylbenzene. The VOCs released during both conventional drying and high-temperature drying were the same. However, large amounts of benzene were detected during the high-temperature drying process. During conventional drying of the Russian Pinus sylvestris material, a total of 17 chemical compounds were detected: 7 aldehydes including formaldehyde, 6 terpenes including α-pinene, and 2 additional compounds. The VOCs released during conventional drying and high-temperature drying were the same. However, large amounts of camphene were detected during high-temperature drying. For plantation Pinus sylvestris, the release of VOCs primarily took place at the later stage of conventional drying, and at the earlier stage of high-temperature drying. For Russian Pinus sylvestris, the amount and the release rate of VOCs during conventional drying were extremely low, and the VOCs during high-temperature drying were primarily released at the later stage. The total amount of VOCs released during drying was much higher from the plantation Pinus sylvestris than from Russian Pinus sylvestris material.

The unmanned swarm system (USS) has been seen as a promising technology, and will play an extremely important role in both the military and civilian fields such as military strikes, disaster relief and transportation business. As the “nerve center” of USS, the unmanned swarm communication system (USCS) provides the necessary information transmission medium so as to ensure the system stability and mission implementation. However, challenges caused by multiple tasks, distributed collaboration, high dynamics, ultra-dense and jamming threat make it hard for USCS to manage limited spectrum resources. To tackle with such problems, the machine learning (ML) empowered intelligent spectrum management technique is introduced in this paper. First, based on the challenges of the spectrum resource management in USCS, the requirement of spectrum sharing is analyzed from the perspective of spectrum collaboration and spectrum confrontation. We found that suitable multi-agent collaborative decision making is promising to realize effective spectrum sharing in both two perspectives. Therefore, a multi-agent learning framework is proposed which contains mobile-computing-assisted and distributed structures. Based on the framework, we provide case studies. Finally, future research directions are discussed.

PurposeTo determine the predictive performance of the integrated model based on clinical factors and radiomic features for the accurate identification of clinically significant prostate cancer (csPCa) among Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions.Materials and MethodsA retrospective study of 103 patients with PI-RADS 3 lesions who underwent pre-operative 3.0-T MRI was performed. Patients were randomly divided into the training set and the testing set at a ratio of 7:3. Radiomic features were extracted from axial T2WI, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images of each patient. The minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) feature selection methods were used to identify the radiomic features and construct a radiomic model for csPCa identification. Moreover, multivariable logistic regression analysis was used to integrate the clinical factors with radiomic feature model to further improve the accuracy of csPCa identification, and the two are presented in the form of normogram. The performance of the integrated model was compared with radiomic model and clinical model on testing set.ResultsA total of four radiomic features were selected and used for radiomic model construction producing a radiomic score (Radscore). Radscore was significantly different between the csPCa and the non-csPCa patients (training set: p < 0.001; testing set: p = 0.035). Multivariable logistic regression analysis showed that age and PSA could be used as independent predictors for csPCa identification. The clinical–radiomic model produced the receiver operating characteristic (ROC) curve (AUC) in the testing set was 0.88 (95%CI, 0.75–1.00), which was similar to clinical model (AUC = 0.85; 95%CI, 0.52–0.90) (p = 0.048) and higher than the radiomic model (AUC = 0.71; 95%CI, 0.68–1.00) (p < 0.001). The decision curve analysis implies that the clinical–radiomic model could be beneficial in identifying csPCa among PI-RADS 3 lesions.ConclusionThe clinical–radiomic model could effectively identify csPCa among biparametric PI-RADS 3 lesions and thus could help avoid unnecessary biopsy and improve the life quality of patients.

Coronary artery disease (CAD) is a major contributor to morbidity and mortality worldwide. Myocardial ischemia may occur in patients with normal or non-obstructive CAD on invasive coronary angiography (ICA). The comprehensive evaluation of coronary CT angiography (CCTA) integrated with fractional flow reserve derived from CCTA (CT-FFR) to CAD may be essential to improve the outcomes of patients with non-obstructive CAD. China CT-FFR Study-2 (ChiCTR2000031410) is a large-scale prospective, observational study in 29 medical centers in China. The primary purpose is to uncover the relationship between the CCTA findings (including CT-FFR) and the outcome of patients with non-obstructive CAD. At least 10,000 patients with non-obstructive CAD but without previous revascularization will be enrolled. A 5-year follow-up will be performed. The primary endpoint is the occurrence of major adverse cardiovascular events (MACE), including all-cause mortality, non-fatal myocardial infarct, unplanned revascularization, and hospitalization for unstable angina. Clinical characteristics, laboratory and imaging examination results will be collected to analyze their prognostic value.

Summary: Nowadays, achieving powerful electrochemical energy conversion and storage devices is a major challenge of our society. Wood is a biodegradable and renewable material that naturally has a hierarchical porous structure, excellent mechanical performance, and versatile physicochemical properties. Wood-based materials and its derivatives are endowed with great potential as resources to fabricate advanced materials for energy storage, flexible electronics, and clean energy. Herein, we comprehensively overview the methodologies applied for the synthesis of various electrochemical energy storage systems and devices (e.g., supercapacitor, battery, catalytic hydrogen evolution, etc.), the strategies for tailoring the structures and conductivity, as well as their impact on electrochemical performance (energy and power density and long-term durability). Finally, an outlook of future opportunities and prospects in the synthesis and application of electrochemical energy storage is also presented.

Purpose: This study aimed to develop a radiomics score (Rad-score) extracted from liver and spleen CT images in cirrhotic patients to predict the probability of esophageal variceal rebleeding.Methods: In total, 173 cirrhotic patients were enrolled in this retrospective study. A total of 2,264 radiomics features of the liver and spleen were extracted from CT images. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to select features and generate the Rad-score. Then, the Rad-score was evaluated by the concordance index (C-index), calibration curves, and decision curve analysis (DCA). Kaplan–Meier analysis was used to assess the risk stratification ability of the Rad-score.Results: Rad-scoreLiver, Rad-scoreSpleen, and Rad-scoreLiver−Spleen were independent risk factors for EV rebleeding. The Rad-scoreLiver−Spleen, which consisted of ten features, showed good discriminative performance, with C-indexes of 0.853 [95% confidence interval (CI), 0.776–0.904] and 0.822 (95% CI, 0.749–0.875) in the training and validation cohorts, respectively. The calibration curve showed that the predicted probability of rebleeding was very close to the actual probability. DCA verified the usefulness of the Rad-scoreLiver−Spleen in clinical practice. The Rad-scoreLiver−Spleen showed good performance in stratifying patients into high-, intermediate- and low-risk groups in both the training and validation cohorts. The C-index of the Rad-scoreLiver−Spleen in the hepatitis B virus (HBV) cohort was higher than that in the non-HBV cohort.Conclusion: The radiomics score extracted from liver and spleen CT images can predict the risk of esophageal variceal rebleeding and stratify cirrhotic patients accordingly.

Objectives: Perivascular adipose tissue plays a key role in atherosclerosis, but its effects on the composition of carotid atherosclerotic plaques are unknown. This study aimed to investigate the association between inflammatory carotid artery and intraplaque hemorrhage (IPH) in the carotid artery.Methods: This is a single-center retrospective study. Carotid inflammation was assessed by perivascular fat density (PFD) in 72 participants (mean age, 65.1 years; 56 men) who underwent both computed tomography angiography (CTA) and magnetic resonance imaging (MRI) within 2 weeks. The presence of IPH was assessed with MRI. Carotid stenosis, maximum plaque thickness, calcification, and ulceration were evaluated through CTA. The association between PFD and the occurrence of IPH was studied using generalized estimating equations analysis.Results: Of 156 plaques, 72 plaques (46.2%) had IPH. Plaques with IPH showed higher PFD than those without [−41.4 ± 3.9 vs. −55.8 ± 6.5 Hounsfield unit (HU); p < 0.001]. After age, calcification, degree of stenosis, maximum plaque thickness, and ulceration were adjusted for, PFD (OR, 1.96; 95% CI, 1.41–2.73; p < 0.001) was found to be strongly associated with the presence of IPH.Conclusions: A higher PFD is associated with the presence of IPH in the carotid artery. These findings may provide a novel marker to identify carotid IPH and risk stratification.

ObjectiveTo develop and evaluate a deep learning model (DLM) for predicting the risk stratification of gastrointestinal stromal tumors (GISTs).MethodsPreoperative contrast-enhanced CT images of 733 patients with GISTs were retrospectively obtained from two centers between January 2011 and June 2020. The datasets were split into training (n = 241), testing (n = 104), and external validation cohorts (n = 388). A DLM for predicting the risk stratification of GISTs was developed using a convolutional neural network and evaluated in the testing and external validation cohorts. The performance of the DLM was compared with that of radiomics model by using the area under the receiver operating characteristic curves (AUROCs) and the Obuchowski index. The attention area of the DLM was visualized as a heatmap by gradient-weighted class activation mapping.ResultsIn the testing cohort, the DLM had AUROCs of 0.90 (95% confidence interval [CI]: 0.84, 0.96), 0.80 (95% CI: 0.72, 0.88), and 0.89 (95% CI: 0.83, 0.95) for low-malignant, intermediate-malignant, and high-malignant GISTs, respectively. In the external validation cohort, the AUROCs of the DLM were 0.87 (95% CI: 0.83, 0.91), 0.64 (95% CI: 0.60, 0.68), and 0.85 (95% CI: 0.81, 0.89) for low-malignant, intermediate-malignant, and high-malignant GISTs, respectively. The DLM (Obuchowski index: training, 0.84; external validation, 0.79) outperformed the radiomics model (Obuchowski index: training, 0.77; external validation, 0.77) for predicting risk stratification of GISTs. The relevant subregions were successfully highlighted with attention heatmap on the CT images for further clinical review.ConclusionThe DLM showed good performance for predicting the risk stratification of GISTs using CT images and achieved better performance than that of radiomics model.

PurposeTo establish and validate a radiomics nomogram for preoperatively predicting lymph node (LN) metastasis in periampullary carcinomas.Materials and MethodsA total of 122 patients with periampullary carcinoma were assigned into a training set (n = 85) and a validation set (n = 37). The preoperative CT radiomics of all patients were retrospectively assessed and the radiomic features were extracted from portal venous-phase images. The one-way analysis of variance test and the least absolute shrinkage and selection operator regression were used for feature selection. A radiomics signature was constructed with logistic regression algorithm, and the radiomics score was calculated. Multivariate logistic regression model integrating independent risk factors was adopted to develop a radiomics nomogram. The performance of the radiomics nomogram was assessed by its calibration, discrimination, and clinical utility with independent validation.ResultsThe radiomics signature, constructed by seven selected features, was closely related to LN metastasis in the training set (p < 0.001) and validation set (p = 0.017). The radiomics nomogram that incorporated radiomics signature and CT-reported LN status demonstrated favorable calibration and discrimination in the training set [area under the curve (AUC), 0.853] and validation set (AUC, 0.853). The decision curve indicated the clinical utility of our nomogram.ConclusionOur CT-based radiomics nomogram, incorporating radiomics signature and CT-reported LN status, could be an individualized and non-invasive tool for preoperative prediction of LN metastasis in periampullary carcinomas, which might assist clinical decision making.

BackgroundLung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, with high incidence and mortality. To improve the curative effect and prolong the survival of patients, it is necessary to find new biomarkers to accurately predict the prognosis of patients and explore new strategy to treat high-risk LUAD.MethodsA comprehensive genome-wide profiling analysis was conducted using a retrospective pool of LUAD patient data from the previous datasets of Gene Expression Omnibus (GEO) including GSE18842, GSE19188, GSE40791 and GSE50081 and The Cancer Genome Atlas (TCGA). Differential gene analysis and Cox proportional hazard model were used to identify differentially expressed genes with survival significance as candidate prognostic genes. The Kaplan–Meier with log-rank test was used to assess survival difference. A risk score model was developed and validated using TCGA-LUAD and GSE50081. Additionally, The Connectivity Map (CMAP) was used to predict drugs for the treatment of LUAD. The anti-cancer effect and mechanism of its candidate drugs were studied in LUAD cell lines.ResultsWe identified a 5-gene signature (KIF20A, KLF4, KRT6A, LIFR and RGS13). Risk Score (RS) based on 5-gene signature was significantly associated with overall survival (OS). Nomogram combining RS with clinical pathology parameters could potently predict the prognosis of patients with LUAD. Moreover, gliclazide was identified as a candidate drug for the treatment of high-RS LUAD. Finally, gliclazide was shown to induce cell cycle arrest and apoptosis in LUAD cells possibly by targeting CCNB1, CCNB2, CDK1 and AURKA.ConclusionThis study identified a 5-gene signature that can predict the prognosis of patients with LUAD, and Gliclazide as a potential therapeutic drug for LUAD. It provides a new direction for the prognosis and treatment of patients with LUAD.

Although the systemic property of neonicotinoid (neonics) has become the most widely used insecticide worldwide since late 1990s, the current literature offers limited information about the human dietary intake and the potential risks of neonics. In this study, we aimed to assess the cumulative risk of total neonics intakes through fruit and vegetable consumption in 58 children ages 8–12 participated in the Hangzhou China (HZC) study over 5 consecutive weekends. Individual neonic residues in each food item were aggregated using the relative potency factor approach into a single metric (IMIRPF), representing dietary intakes of imidacloprid-equivalent total neonics. We then estimated the average daily intake (ADI) of total neonics through fruit and vegetable consumption and evaluated the cumulative dietary risk of neonics. All of the 123 samples were detected with at least one neonic. Commonly consumed foods, such as carrots, green vegetables, baby cabbage, and apple were found with more than 6 neonics. The estimated ADIs of total neonics vegetable and fruit consumption using the mean IMIRPF for apples and green vegetables, two most consumed food items, were 237.1*10−6 and 106.8*10−6 mg/kg/day, respectively. Although the estimated ADIs were below the current chronic reference dose (cRfD) of imidacloprid, we have stipulated the possible future downward revision of cRfD. The potential health risk of neonics to children via dietary exposure should raise more public concern considering the increase use of neonics and the ubiquitous presence in fruits and vegetables. Keywords: Neonicotinoids, Dietary intake, Cumulative dietary risk, Relative potency factor, Reference dose

This paper investigates the problem of anti-jamming communication in dynamic and intelligent jamming environment. A sequential deep reinforcement learning algorithm (SDRLA) without prior information is proposed, and raw spectrum information is used as the input of SDRLA. The proposed SDRLA algorithm mainly contains two parts: Firstly, deep learning and sliding window principle are introduced to identify jamming patterns; Secondly, reinforcement learning is carried out to make on-line channel selection based on recognized jamming patterns. In addition, channel switching cost is introduced for the purpose of formulating the trade-off relationship between throughput and overhead. Taking advantage of both deep learning and reinforcement learning, this method can realize rapid and effective anti-jamming channel selection with no need for modeling the jammer's characteristics. Simulation results show the convergence and effectiveness of the proposed SDRLA algorithm. Compared with single-mode reinforcement learning, our approach can reach better convergence performance and higher utility.

Previous studies have revealed highly reproducible patterns of temporally lagged brain activity in healthy human adults. However, it is unknown whether temporal organization of intrinsic activity is altered in migraines or if it relates to migraine chronification. In this resting-state functional magnetic resonance imaging study, temporal features of intrinsic activity were investigated using resting-state lag analysis, and 39 episodic migraine patients, 17 chronic migraine patients, and 35 healthy controls were assessed. Temporally earlier intrinsic activity in the hippocampal complex was revealed in the chronic migraine group relative to the other two groups. We also found earlier intrinsic activity in the medial prefrontal cortex in chronic compared with episodic migraines. Both migraine groups showed earlier intrinsic activity in the lateral temporal cortex and sensorimotor cortex compared with the healthy control group. Across all patients, headache frequency negatively correlated with temporal lag of the medial prefrontal cortex and hippocampal complex. Disrupted propagation of intrinsic activity in regions involved in sensory, cognitive and affective processing of pain may contribute to abnormal brain function during migraines. Decreased time latency in the lateral temporal cortex and sensorimotor cortex may be common manifestations in episodic and chronic migraines. The temporal features of the medial prefrontal cortex and hippocampal complex were associated with migraine chronification.

Methane reforming with carbon dioxide (DRM) is one promising way to achieve carbon neutrality and convert methane to syngas for high-value chemical production. Catalyst development with better performance is the key to its potential large-scale industrial application due to its deactivation caused by carbon deposition and metal sintering. Hence, a Ni/CeO2 catalyst (Ni/CeO2-M) with higher CO2 conversion and better stability is prepared, supported on CeO2 precipitated via a novel microimpinging stream reactor. A series of ex-situ or in-situ characterizations, such as CO titration measurements, two-step transient surface reaction (two-step TSR), CO2 and CH4 temperature-programmed surface reaction (CO2-TPSR and CH4-TPSR), X-ray absorption fine structure (XAFS), and in-situ Raman spectroscopy study, were used to investigate its structure and mechanism. In contrast to Ni supported on commercial CeO2 (Ni/CeO2-C), the Ni/CeO2-M catalyst with stronger lattice oxygen mobility and higher oxygen storage capacity enhances its CO2 activation ability and carbon deposition. The Ni particle size of the Ni/CeO2-M catalyst decreased, and a higher oxidation state was obtained due to the strong metal–support interaction. Besides the reaction performance improvement of the Ni/CeO2-M catalyst, the novel microimpinging stream reactor could achieve catalyst continuous production with a high preparation efficiency. This work provides a novel method for the high-performance catalyst preparation for DRM reaction and its mechanism study gives a deep insight into high-performance catalyst development via bottom-up study.

Individuals with subjective cognitive decline (SCD) are more likely to develop into Alzheimer disease (AD) in the future. Resting-state functional magnetic resonance imaging (rs-fMRI) studies have shown alterations of intrinsic brain activity (IBA) in SCD individuals. However, rs-fMRI studies to date have mainly focused on static characteristics of IBA, with few studies reporting dynamics- and concordance-related changes in IBA indices in SCD individuals. To investigate these aberrant changes, a temporal dynamic analysis of rs-fMRI data was conducted on 94 SCD individuals (71.07 ± 6.18 years, 60 female), 75 (74.36 ± 8.42 years, 35 female) mild cognitive impairment (MCI) patients, and 82 age-, gender-, and education-matched controls (NCs; 73.88 ± 7.40 years, 49 female) from the Alzheimer's Disease Neuroimaging Initiative database. The dynamics and concordance of the rs-fMRI indices were calculated. The results showed that SCD individuals had a lower amplitude of low-frequency fluctuations dynamics in bilateral hippocampus (HP)/parahippocampal gyrus (PHG)/fusiform gyrus (FG) and bilateral cerebellum, a lower fractional amplitude of low-frequency fluctuation dynamics in bilateral precuneus (PreCu) and paracentral lobule, and a lower regional homogeneity dynamics in bilateral cerebellum, vermis, and left FG compared with the other two groups, whereas those in MCI patients were higher (Gaussian random field–corrected, voxel-level P < 0.001, cluster-level P < 0.05). Furthermore, SCD individuals had higher concordance in bilateral HP/PHG/FG, temporal lobe, and left midcingulate cortex than NCs, but those in MCI were lower than those in NCs. No correlation between concordance values and neuropsychological scale scores was found. SCD individuals showed both dynamics and concordance-related alterations in IBA, which indicates a compensatory mechanism in SCD individuals. Temporal dynamics analysis offers a novel approach to capturing brain alterations in individuals with SCD.

Zeolitic imidazolate framework-8 (ZIF-8) was evenly loaded on the surface of TiO2 doped with KI, using a solvent synthesis method, in order to produce a ZIF-8@TiO2 (KI) adsorption photocatalyst with good adsorption and photocatalytic properties. The samples were characterized by XRD, SEM, EDX, XPS, BET and UV-Vis. The photocatalytic efficiency of the material was obtained by photocatalytic tests. The results indicate that the doping with I inhibited the grain growth and reduced the crystallite size of TiO2, reduced the band gap width and improved the utilization rate for light. TiO2 (KI) was a single crystal of anatase titanium dioxide. The combination of ZIF-8 and TiO2 (KI) improved the specific surface area and increased the reaction site. The ZIF-8@TiO2 (KI) for Congo red was investigated to validate its photocatalytic performance. The optimal concentration of Congo red solution was 30 mg/L, and the amount of catalyst was proportional to the degradation efficiency. The degradation efficiency of ZIF-8@TiO2 (5%KI) was 76.42%, after being recycled four times.

Background Mapping techniques using cardiac magnetic resonance imaging have significantly improved the diagnostic accuracy for myocarditis with focal myocardial injuries. The aim of our study was to determine whether T1 and T2 mapping techniques could identify diffuse myocardial injuries in “normal-appearing” myocardium in pediatric patients with clinically suspected myocarditis and to evaluate the associations between diffuse myocardial injuries and cardiac function parameters. Methods Forty-six subjects were included in this study: 20 acute myocarditis patients, 11 subacute/chronic myocarditis patients and 15 control children. T2 values, native T1 values and the extracellular volume (ECV) of “normal-appearing” myocardium were compared among the three groups of patients. Associations between diffuse myocardial injuries and cardiac function parameters were also evaluated. Results The ECV of “normal-appearing” myocardium was significantly higher in the subacute/chronic myocarditis group than in the control group (30.1 ± 0.9 vs 27.0 ± 0.6, P =0.004). No significant differences in T1 and T2 values between the acute myocarditis and control groups were found. In the subacute/chronic myocarditis group, a significant association between ECV and left ventricle ejection fraction was found (P=0.03). Conclusions Diffuse myocardial injuries are likely to occur in subacute/chronic myocarditis patients with prolonged inflammatory responses. Mapping techniques have great value for the diagnosis and monitoring of myocarditis.

ObjectivesTo develop and validate a radiomics nomogram to improve prediction of recurrence and metastasis risk in T1 stage clear cell renal cell carcinoma (ccRCC).MethodsThis retrospective study recruited 168 consecutive patients (mean age, 53.9 years; range, 28–76 years; 43 women) with T1 ccRCC between January 2012 and June 2019, including 50 aggressive ccRCC based on synchronous metastasis or recurrence after surgery. The patients were divided into two cohorts (training and validation) at a 7:3 ratio. Radiomics features were extracted from contrast enhanced CT images. A radiomics signature was developed based on reproducible features by means of the least absolute shrinkage and selection operator method. Demographics, laboratory variables (including sex, age, Fuhrman grade, hemoglobin, platelet, neutrophils, albumin, and calcium) and CT findings were combined to develop clinical factors model. Integrating radiomics signature and independent clinical factors, a radiomics nomogram was developed. Nomogram performance was determined by calibration, discrimination, and clinical usefulness.ResultsTen features were used to build radiomics signature, which yielded an area under the curve (AUC) of 0.86 in the training cohort and 0.85 in the validation cohort. By incorporating the sex, maximum diameter, neutrophil count, albumin count, and radiomics score, a radiomics nomogram was developed. Radiomics nomogram (AUC: training, 0.91; validation, 0.92) had higher performance than clinical factors model (AUC: training, 0.86; validation, 0.90) or radiomics signature as a means of identifying patients at high risk for recurrence and metastasis. The radiomics nomogram had higher sensitivity than clinical factors mode (McNemar’s chi-squared = 4.1667, p = 0.04) and a little lower specificity than clinical factors model (McNemar’s chi-squared = 3.2, p = 0.07). The nomogram showed good calibration. Decision curve analysis demonstrated the superiority of the nomogram compared with the clinical factors model in terms of clinical usefulness.ConclusionThe CT-based radiomics nomogram could help in predicting recurrence and metastasis risk in T1 ccRCC, which might provide assistance for clinicians in tailoring precise therapy.

Background: Hypothesis-driven functional connectivity (FC) analyses have revealed abnormal functional interaction of regions or networks involved in pain processing in episodic migraine patients. We aimed to investigate the resting-state FC patterns in episodic migraine by combining data-driven voxel-wise degree centrality (DC) calculation and seed-based FC analysis.Methods: Thirty-nine patients suffering from episodic migraine without aura and 35 healthy controls underwent clinical assessment and functional MRI. DC was analyzed voxel-wise and compared between groups, and FC of regions with DC differences were further examined using a seed-based approach.Results: Compared with the control group, the migraine group showed increased and decreased DC in the right posterior insula and left crus I, respectively. Seed-based FC analyses revealed that migraine patients demonstrated increased right posterior insula connections with the postcentral gyrus, supplementary motor area/paracentral lobule, fusiform gyrus and temporal pole. The left crus I showed decreased FC with regions of the default mode network (DMN), including the medial prefrontal cortex (mPFC), angular gyrus, medial and lateral temporal cortex in patients with migraine. Furthermore, pain intensity positively correlated with DC in the right amygdala/parahippocampal gyrus, and migraine frequency negatively correlated with FC between the left crus I and mPFC.Conclusion: Patients with episodic migraine without aura have increased FC with the right posterior insula and decreased FC within the DMN, which may underlie disturbed sensory integration and cognitive processing of pain. The left crus I-mPFC connectivity may be a useful biomarker for assessing migraine frequency.

Heavy metal wastewater treatment is a huge problem facing human beings, and the application degree of Salix psammophila resources produced by flat stubble is low. Therefore, it is very important to develop high-value products of Salix psammophila resources and apply them in the removal heavy metal from effluent. In this work, we extracted the cellulose from Salix psammophila, and cellulose nanofibers (CNFs) were prepared through TEMPO oxidation/ultrasound. The aerogel spheres derived from Salix psammophila (ASSP) were prepared with the hanging drop method. The experimental results showed that the Cu(II) adsorption capacity of the ASSP composite (267.64 mg/g) doped with TOCNF was significantly higher than that of pure cellulose aerogel spheres (52.75 mg/g). The presence of carboxyl and hydroxyl groups in ASSP enhanced the adsorption capacity of heavy metals. ASSP is an excellent heavy metal adsorbent, and its maximum adsorption values for Cu(II), Mn(II), and Zn(II) were found to be 272.69, 253.25, and 143.00 mg/g, respectively. The abandoned sand shrub resource of SP was used to adsorb heavy metals from effluent, which provides an important reference value for the development of forestry in this sandy area and will have a great application potential in the fields of the adsorption of heavy metals in soil and antibiotics in water.

Abstract In this paper, we provide an effective multiuser transmission scheme in three-dimensional (3D) massive multiple-input multiple-output (MIMO) cellular systems, where the full-duplex (FD) base station (BS) equips two separate large-scale uniform planar antenna array (UPA). In order to reduce the computational and implementation complexity, we investigate the characteristic of the beam-domain (BD) 3D massive MIMO channels and self-interference (SI) channel. We propose the 3D multiuser beamspace transmission (MUBT) scheme that requires the spatial angular information of the users and the SI channel. We show that, due to the reduced dimension property of the effective beamspace channel, the overhead for channel estimation is reduced. Furthermore, a user scheduling algorithm is proposed to enable the 3D MUBT scheme in the FD systems. Finally, both the theoretical analysis and simulation results show the the SI can be effectively reduced and demonstrate the effectiveness and superiority of the proposed 3D MUBT scheme on spectral efficiency compared with the conventional half-duplex (HD) and FD transmission schemes.

Background/Aims: The transcription cofactor limb-bud and heart (LBH) is involved in embryonic development. However, its role in human lung cancer, especially lung adenocarcinoma (LUAD), remains unclear. Methods: A public database and tissue microarray (TMA) were used to compare differences in LBH expression and its relationship with clinical characteristics. Tissue from an additional 70 LUAD patients with follow-up records was used to explore the correlation of LBH expression with prognosis. Cellular and molecular studies validated the role of LBH in LUAD growth and invasion. Results: LBH was significantly down-regulated in lung cancer tissue samples and was correlated with the prognosis and clinical characteristics of lung cancer patients based on a public database and TMA. Survival analysis revealed that LBH-negative expression was associated with poor overall survival of LUAD patients (P = 0.021). Cox regression analysis showed that LBH expression status was a favorable independent prognostic factor (hazard ratio = 0.120, 95% confidence interval = 0.016–0.894, P = 0.039). LBH knockdown accelerated LUAD cell proliferation, migration, and invasion. Furthermore, bioinformatics analysis indicated that LBH was significantly related to the cell adhesion pathway. Western blot analysis confirmed that LBH could regulate the expression of integrin family members (integrin-α1, integrin-α2, integrin-α4, integrin-αv, and integrin-β4). Conclusion: Our data suggest that LBH plays an important role in lung cancer. Importantly, LBH is an independent prognostic factor in LUAD and can attenuate cell growth and invasion. LBH may be a potential prognostic biomarker in LUAD patients.

During May–August 2016, mumps virus genotype K was detected in 12 Vietnam citizens who entered China at the Shuikou border crossing and 1 girl from China. We provide evidence that mumps genotype K is circulating in Vietnam and was imported to China from Vietnam.

Zeolitic imidazolate framework-8 (ZIF-8) was doped with a rare-earth metal, Eu, using a solvent synthesis method evenly on the surface of a mixed-crystal TiO2(Mc-TiO2) structure in order to produce a core–shell structure composite ZIF-8(Eu)@Mc-TiO2 adsorption photocatalyst with good adsorption and photocatalytic properties. The characterisation of ZIF-8(Eu)@Mc-TiO2 was performed via X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Brunauer–Emmett–Teller analysis (BET) and ultraviolet–visible light differential reflectance spectroscopy (UV-DRs). The results indicated that Eu-doped ZIF-8 was formed evenly on the Mc-TiO2 surface, a core–shell structure formed and the light-response range was enhanced greatly. The ZIF-8(Eu)@Mc-TiO2 for basic fuchsin was investigated to validate its photocatalytic performance. The effect of the Eu doping amount, basic fuchsin concentration and photocatalyst dosage on the photocatalytic efficiency were investigated. The results revealed that, when 5%-Eu-doped ZIF-8(Eu)@Mc-TiO2 (20 mg) was combined with 30 mg/L basic fuchsin (100 mL) under UV irradiation for 1 h, the photocatalytic efficiency could reach 99%. Further, it exhibited a good recycling performance. Thus, it shows certain advantages in its degradation rate and repeatability compared with previously reported materials. All of these factors suggested that, in an aqueous medium, ZIF-8(Eu)@Mc-TiO2 is an eco-friendly, sustainable and efficient material for the photocatalytic degradation of basic fuchsin.

Lignocellulose (LCE) was ultrasonically treated and intercalated into magnesium aluminum silicate (MOT) clay to prepare a nano-lignocellulose magnesium aluminum silicate polymer gel (nano-LCE-MOT) for the removal of Zn (II) from aqueous solution. The product was characterised using nitrogen adsorption/desorption isotherm measurements, Fourier-transform infrared spectroscopy, scanning electron microscopy and energy-dispersive X-ray spectroscopy. The conditions for the adsorption of Zn (II) on nano-LCE-MOT were screened, and adsorption kinetics and isotherm model analysis were carried out to explore the adsorption mechanism and achieve the optimal adsorption of Zn (II). Optimal adsorption was achieved at an initial Zn (II) concentration of 800 mg/L at 60 °C in 160 min at a pH of 4.52. The adsorption kinetics were explored using a pseudo-second-order model, with the isotherm adsorption equilibrium found to conform to the Langmuir model. The maximum adsorption capacity of the nano-LCE-MOT polymer gel toward Zn (II) is 513.48 mg/g. The materials with adsorbed Zn (II) were desorbed using different media, with HCl found to be the most ideal medium to desorb Zn (II). The optimal desorption of Zn (II) was achieved in 0.08 mol/L HCl solution at 65 °C in 60 min. Under these conditions, Zn (II) was almost completely desorbed from the adsorbents, with the adsorption effect after cycling being slightly different from that of the initial adsorption.

Background/Aims: Myocardial infarction (MI) is a leading cause of morbidity and mortality. Here, we sought to explore the potential role and underlying mechanism of miR-145 in MI. Methods: H9c2 cells were cultured under persistent hypoxia to simulate MI. The hypoxia-induced injury was assessed on the basis of cell viability, migration, invasion and apoptosis. The expression of miR-145 was evaluated by qRT-PCR and the influence of aberrantly expressed miR-145 on H9c2 cells under hypoxia was also estimated. Utilizing bioinformatics methods, the target genes of miR-145 were verified by luciferase reporter assay. Then, effects of abnormally expressed target gene on miR-145 silenced H9c2 cells were assessed. Finally, the phosphorylation levels of key kinases in the phosphatidylinositol-3-kinase (PI3K)/AKT and the mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) pathways were detected by Western blot analysis. Results: Hypoxia remarkably lowered viability, migration and invasion but promoted cell apoptosis. Meantime, the miR-145 level was up-regulated in H9c2 cells under hypoxia. Following experiments suggested that hypoxia-induced injury was exacerbated by miR-145 overexpression while was alleviated by miR-145 silence. Rac1 was predicted and further validated to be a target gene of miR-145. The influence of miR-145 silencing on H9c2 cells under hypoxia could be reversed by down-regulation of Rac1. Additionally, the phosphorylation levels of PI3K, AKT, MAPK and ERK were all elevated in miR-145 silenced cells and these alterations were reversed by down-regulation of Rac1. Conclusion: miR-145 silencing could protect H9c2 cells against hypoxia-induced injury by targeting Rac1, in which PI3K/AKT and MAPK/ERK pathways might be involved.

Background/Aims: The hanging drop technique is a well-established method used in culture of animal tissues. However, this method has not been used in adult kidney tissue culture yet. This study was to explore the feasibility of using this technique for culturing adult kidney cortex to study the time course of RNA viability in the tubules and vasculature, as well as the tissue structural integrity. Methods: In each Petri dish with the plate covered with sterile buffer, a section of mouse renal cortex was cultured within a drop of DMEM culture medium on the inner surface of the lip facing downward. The tissue were then harvested at each specific time points for Real-time PCR analysis and histological studies. Results: The results showed that the mRNA level of most Na+ related transporters and cotransporters were stably maintained within 6 hours in culture, and that the mRNA level of most receptors found in the vasculature and glomeruli were stably maintained for up to 9 days in culture. Paraffin sections of the cultured renal cortex indicated that the tubules began to lose tubular integrity after 6 hours, but the glomeruli and vasculatures were still recognizable up to 9 days in culture. Conclusions: We concluded that adult kidney tissue culture by hanging drop method can be used to study gene expressions in vasculature and glomeruli.

Abstract In this paper, we consider a multi-user full-duplex (FD) massive multiple-input multiple-output (MIMO) system. The FD base station (BS) is equipped with large-scale antenna arrays, while each FD user is equipped with two antennas (one for transmission and the other one for reception). We assume that the channel state information (CSI) is imperfect, and no instantaneous CSI of loop interference (LI) channel is obtained. On the basis of low-complexity uplink beamforming and downlink precoding techniques, i.e. maximum-ratio combining/maximum-ratio transmission (MRC/MRT) and zero-forcing reception/zero-forcing transmission (ZFR/ZFT), the asymptotic expressions of signal-to-interference-plus-noise ratio (SINR) of uplink and downlink are derived respectively when the number of antennas of the BS tends to infinity. Based on the asymptotic SINR expressions, we first analyse the spectral efficiency (SE) performance assuming that the generalized power scaling scenario is adopted. Through the theoretical derivation, it is shown that the detrimental impact of the LI can be eliminated by the very large number of antennas at the BS if the power scaling scenario is appropriately applied, as well as the interference caused by the imperfect channel estimation, the multi-user interference (MUI) and inter-user interference (IUI). Then, we propose power allocation (PA) scenarios to maximize the energy efficiency (EE) and the sum SE with the constraint of maximum powers at the BS and users. The simulation results verify the accuracy of the asymptotic method, we also validate the effectiveness of the EE and the sum SE maximization PA algorithms. We show that adopting the PA scheme to maximize the sum SE can make the multi-user FD massive MIMO system outperform the half-duplex (HD) counterpart regardless of the level of LI.

In this paper, we investigate the secure transmission of wireless relaying systems with multidestinations and an eavesdropper (Eve) in Nakagami-m fading channels. To protect the confidential message from leaking to the Eve, an intentional interference is sent from a selected destination. We propose two jammer selection schemes under two typical communication scenarios: the channel state information (CSI) of the Eve is unknown, where ajammer is selected based on the CSI between the selected legitimate receiver and the other destination users and the CSI of the Eve is available, where a jammer is selected based on the CSI between the Eve and the other destination users. To assess the performance of the two proposed schemes, we first derive the exact closed-form expressions of intercept probability and outage probability to evaluate the security and the reliability of the system, respectively. In addition, to evaluate the security and reliability as a whole, we propose a new definition of the security-reliability tradeoff, which allows us to easily optimize the power allocation and improve the performance. Finally, simulation results are provided to verify the availability of the proposed schemes.

Objective: To differentiate prostate cancer lesions in transition zone by diffusion-weighted-MRI (DW-MRI). Methods: Data from a total of 63 patients who underwent preoperative DWI (b of 0â1000 s/mm2) were prospectively collected and processed by a monoexponential (DWI) model and compared with a biexponential (IVIM) model for quantitation of apparent diffusion coefficients (ADCs), perfusion fraction f, diffusivity D and pseudo-diffusivity D*. Histogram analyses were performed by outlining entire-tumor regions of interest (ROIs). These parameters (separately and combined in a logistic regression model) were used to differentiate lesions depending on histopathological analysis of Magnetic Resonance/transrectal Ultrasound (MR/TRUS) fusion-guided biopsy. The diagnostic ability of differentiate the PCa from BHP in TZ was analyzed by ROC regression. Histogram analysis of quantitative parameters and Gleason score were assessed with Spearman correlation. Results: Thirty (30 foci) cases of PCa in PZ and 33 (36 foci) cases of BPH were confirmed by pathology. Mean ADC, median ADC, 10th percentile ADC, 90th percentile ADC, kurtosis and skewness of ADC and mean D values, median D and 90th percentile D differed significantly between PCa and BHP in TZ. The highest classification accuracy was achieved by the mean ADC (0.841) and mean D (0.809). A logistic regression model based on mean ADC and mean D led to an AUC of 0.873, however, the difference is not significant. There were 7 Gleason 6 areas, 9 Gleason 7 areas, 8 Gleason 8 areas, 5 Gleason 9 areas and 2 Gleason 10 areas detected from the 31 prostate cancer areas, the mean Gleason value was(7.5 ± 1.2). The mean ADC and mean D had correlation with Gleason score(r = â0.522 and r = â0.407 respectively, PÂ