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Emotional intelligence (EI) is one's ability to monitor one's own and other's emotions and the use of emotional information to enhance thought and action. Previous behavioral studies have shown that EI is separable into trait EI and ability EI, which are known to have distinct characteristics at the behavioral level. A relevant and unanswered question is whether both forms of EI have a dissociable neural basis. Previous studies have individually explored the neural underpinnings of trait EI and ability EI, but there has been no direct comparison of the neural mechanisms underlying these two types of emotional intelligence. The present study addresses this question by using resting-state fMRI to examine the correlational pattern between the regional amplitude of low-frequency fluctuations (ALFF) of the brain and individuals' trait EI and ability EI scores. We found that trait EI scores were positively correlated with the ALFF in the bilateral superior temporal gyrus, and negatively correlated with the ALFF in the ventral medial prefrontal cortex. In contrast, ability EI scores were positively correlated with the ALFF in the insula. Taken together, these results provide preliminary evidence of dissociable neural substrates between trait EI and ability EI. [ABSTRACT FROM AUTHOR]

Bacterial species within the Acinetobacter baumannii-calcoaceticus (Acb) complex are very similar and are difficult to discriminate. Misidentification of these species in human infection may lead to severe consequences in clinical settings. Therefore, it is important to accurately discriminate these pathogens within the Acb complex. Raman spectroscopy is a simple method that has been widely studied for bacterial identification with high similarities. In this study, we combined surfaced-enhanced Raman spectroscopy (SERS) with a set of machine learning algorithms for identifying species within the Acb complex. According to the results, the support vector machine (SVM) model achieved the best prediction accuracy at 98.33% with a fivefold cross-validation rate of 96.73%. Taken together, this study confirms that the SERS-SVM method provides a convenient way to discriminate between A. baumannii, Acinetobacter pittii, and Acinetobacter nosocomialis in the Acb complex, which shows an application potential for species identification of Acinetobacter baumannii-calcoaceticus complex in clinical settings in near future. [ABSTRACT FROM AUTHOR]

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent gastrointestinal malignancies with high mortality worldwide. Emerging evidence indicates that long noncoding RNAs (lncRNAs) are involved in human cancers, including ESCC. However, the detailed mechanisms of lncRNAs in the regulation of ESCC progression remain incompletely understood. LUESCC was upregulated in ESCC tissues compared with adjacent normal tissues, which was associated with gender, deep invasion, lymph node metastasis, and poor prognosis of ESCC patients. LUESCC was mainly localized in the cytoplasm of ESCC cells. Knockdown of LUESCC inhibited cell proliferation, colony formation, migration, and invasion in vitro and suppressed tumor growth in vivo. Mechanistic investigation indicated that LUESCC functions as a ceRNA by sponging miR-6785-5p to enhance NRSN2 expression, which is critical for the malignant behaviors of ESCC. Furthermore, ASO targeting LUESCC substantially suppressed ESCC both in vitro and in vivo. Collectively, these data demonstrate that LUESCC may exerts its oncogenic role by sponging miR-6785-5p to promote NRSN2 expression in ESCC, providing a potential diagnostic marker and therapeutic target for ESCC patients. [ABSTRACT FROM AUTHOR]

Seismic inversion is one of the fundamental techniques for solving geophysics problems. To obtain the elastic parameters or petrophysical parameters, it is necessary to establish a direct or indirect mapping that is usually nonlinear between the observed data and the inversion parameters in seismic inversion. The traditional model-based inversion method, which is calculating complex and expensive, relies on strict physics theories. Neural networks are an excellent artificial intelligence method for establishing nonlinear mapping. Theoretically, any linear and nonlinear functions can be fitted with neural networks. Compared with model-based inversion methods, the inversion efficiency and accuracy can be improved remarkably using neural networks with their powerful ability to discover and extract features from big data. By reviewing the application of fully-connected neural networks, probabilistic neural networks, convolutional neural networks, recurrent neural networks, generative neural networks, and physics-based neural networks in seismic inversion, we provide a comprehensive overview of neural network methods to seismic inversion, including the basic principles of different neural networks, types of seismic inversion, seismic datasets, and the general framework of neural networks for seismic inversion. In addition, the future trends of seismic inversion based on neural networks are also discussed, including the application of image segmentation networks and generative adversarial networks in seismic inversion. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate whether MRI-based T stage (TMRI), [18F]FDG PET/CT-based N (NPET/CT), and M stage (MPET/CT) are superior in NPC patients' prognostic stratification based on long-term survival evidences, and whether TNM staging method involving TMRI + NPET/CT + MPET/CT could improve NPC patients' prognostic stratification. Methods: From April 2007 to December 2013, 1013 consecutive untreated NPC patients with complete imaging data were enrolled. All patients' initial stages were repeated based on (1) the NCCN guideline recommended "TMRI + NMRI + MPET/CT" ("MMP") staging method; (2) the traditional "TMRI + NMRI + Mconventional work-up (CWU)" ("MMC") staging method; (3) the single-step "TPET/CT + NPET/CT + MPET/CT" ("PPP") staging method; or (4) the "TMRI + NPET/CT + MPET/CT" ("MPP") staging method recommended in present research. Survival curve, ROC curve, and net reclassification improvement (NRI) analysis were used to evaluate the prognosis predicting ability of different staging methods. Results: [18F]FDG PET/CT performed worse on T stage (NRI = − 0.174, p < 0.001) but better on N (NRI = 0.135, p = 0.004) and M stage (NRI = 0.126, p = 0.001). The patients whose N stage upgraded by [18F]FDG PET/CT had worse survival (p = 0.011). The "TMRI + NPET/CT + MPET/CT" ("MPP") method performed better on survival prediction when compared with "MMP" (NRI = 0.079, p = 0.007), "MMC" (NRI = 0.190, p < 0.001), or "PPP" method (NRI = 0.107, p < 0.001). The "TMRI + NPET/CT + MPET/CT" ("MPP") method could reclassify patients' TNM stage to a more appropriate stage. The improvement is significant in patients with more than 2.5-years follow-up according to the time-dependent NRI values. Conclusions: The MRI is superior to [18F]FDG PET/CT in T stage, and [18F]FDG PET/CT is superior to CWU in N/M stage. The "TMRI + NPET/CT + MPET/CT" ("MPP") staging method could significantly improve NPC patients' long-term prognostic stratification. Clinical relevance statement: The present research provided long-term follow-up evidence for benefits of MRI and [18F]FDG PET/CT in TNM staging for nasopharyngeal carcinoma, and proposes a new imaging procedure for TNM staging incorporating MRI-based T stage and [18F]FDG PET/CT-based N and M stage, which significantly improves long-term prognostic stratification for patients with NPC. Key Points: • The long-term follow-up evidence of a large-scale cohort was provided to evaluate the advantages of MRI, [18F]FDG PET/CT, and CWU in the TNM staging of nasopharyngeal carcinoma. • A new imaging procedure for TNM stage of nasopharyngeal carcinoma was proposed. [ABSTRACT FROM AUTHOR]

Objectives: This study focused on developing and validating a nomogram to predict the overall survival (OS) of patients with nasopharyngeal carcinoma (NPC) without distant metastasis based on their clinical characteristics, serum biomarkers, and presence of nasopharyngeal (NP) necrosis. Methods: This study included 9298 patients with NPC. Patients from January 2009 to December 2014 were randomly categorized into the training cohort and validation cohort A. Validation cohort B, whose data were collected from January 2015 to December 2017, was also included. OS was the primary endpoint of this study. Cox regression analysis was used to detect independent risk variables. Decision curve analysis, calibration curve, time-dependent receiver operating characteristic (ROC) curve, and concordance index (C-index) were used to evaluate the performance of the nomogram model. Results: A total of 267 patients developed NP necrosis after the first routine radiotherapy. After radiotherapy, patients with NP necrosis had significantly lower OS than other patients in all three cohorts (p < 0.001). Eleven factors, including NP necrosis, were involved in the nomogram, which had favorable discrimination and calibration with a C-index of 0.768 in the training cohort, 0.749 in validation cohort A, and 0.739 in validation cohort B. The nomogram exhibited a significantly larger area under the ROC curve for predicting OS than the TNM stage and Epstein-Barr virus (EBV) DNA (p < 0.001). Conclusion: Compared with the TNM system and EBV DNA, we established a nomogram model with an accurate prognostic prediction for patients with NPC, which might help with patient management in NPC. Key Points: • This study included 9298 patients with NPC, and 11 factors were involved in the final model. • The nomogram had a significantly higher C-index and area under the ROC curve than the TNM stage and EBV DNA. • We established the first nomogram model for NPC involving the occurrence of NP necrosis, which was valuable for providing individual counseling and clinical assessments. [ABSTRACT FROM AUTHOR]

Synchronizers are the heart for vehicles. The reliability of synchronizer ring in the gearbox affects the operation of the entire systems of vehicles. In this paper, a pre-failure of synchronizer ring made of brass was investigated. Macro and micro analysis, chemical composition analysis, mechanical property test and finite element method were conducted on the synchronizer ring. The analysis results showed that the content of element in the micro area of the outer ring exceeded the standard, which caused the increases of hardness and brittleness of material. The resisting crack propagation ability of material was reduced due to the element segregation. It was concluded that the synchronizer ring was fractured due to the high hardness and brittleness of material, combined with the stress concentration. Finally, countermeasures were proposed to address similar problems. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the clinical benefit of salvage allogeneic hematopoietic stem cell transplantation (allo-HSCT) in combination with enhanced myeloablative preconditioning in the treatment of refractory liver and spleen T-cell lymphomas. A retrospective analysis was performed on three patients (with refractory liver and spleen T-cell lymphomas) who have been treated with salvage allo-HSCT combined with enhanced myeloablative preconditioning. One of three patients had a liver biopsy; the other two underwent bone marrow analysis using morphology, immunology, cytogenetics, and molecular biology. All three patients were resistant to chemotherapy and with a high tumor load, so a new total body irradiation/splenic region irradiation/GEM/CLAG/ATG preconditioning regimen was conducted and followed with salvage HSCT. Two patients received haploidentical-donor hematopoietic stem cell transplants, and one received an unrelated full-donor hematopoietic stem cell transplant. The three patients survived disease-free until May 2021. Clinically, hepatosplenic T-cell lymphoma (HSTCL) is rare, with a poor prognosis and chemotherapy response. Based on the present study's encouraging clinical results, salvage allo-HSCT in conjunction with an enhanced myeloablative preconditioning regiment may be an effective and safe treatment for HSTCL. [ABSTRACT FROM AUTHOR]

Purpose: Although treatment planning and individualized dose application for emerging prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) are generally recommended, it is still difficult to implement in practice at the moment. In this study, we aimed to prove the concept of pretherapeutic prediction of dosimetry based on imaging and laboratory measurements before the RLT treatment. Methods: Twenty-three patients with metastatic castration-resistant prostate cancer (mCRPC) treated with 177Lu-PSMA I&T RLT were included retrospectively. They had available pre-therapy 68 Ga-PSMA-HEBD-CC PET/CT and at least 3 planar and 1 SPECT/CT imaging for dosimetry. Overall, 43 cycles of 177Lu-PSMA I&T RLT were applied. Organ-based standard uptake values (SUVs) were obtained from pre-therapy PET/CT scans. Patient dosimetry was calculated for the kidney, liver, spleen, and salivary glands using Hermes Hybrid Dosimetry 4.0 from the planar and SPECT/CT images. Machine learning methods were explored for dose prediction from organ SUVs and laboratory measurements. The uncertainty of these dose predictions was compared with the population-based dosimetry estimates. Mean absolute percentage error (MAPE) was used to assess the prediction uncertainty of estimated dosimetry. Results: An optimal machine learning method achieved a dosimetry prediction MAPE of 15.8 ± 13.2% for the kidney, 29.6% ± 13.7% for the liver, 23.8% ± 13.1% for the salivary glands, and 32.1 ± 31.4% for the spleen. In contrast, the prediction based on literature population mean has significantly larger MAPE (p < 0.01), 25.5 ± 17.3% for the kidney, 139.1% ± 111.5% for the liver, 67.0 ± 58.3% for the salivary glands, and 54.1 ± 215.3% for the spleen. Conclusion: The preliminary results confirmed the feasibility of pretherapeutic estimation of treatment dosimetry and its added value to empirical population-based estimation. The exploration of dose prediction may support the implementation of treatment planning for RLT. [ABSTRACT FROM AUTHOR]

Purpose: While sedation is routinely used in pediatric PET examinations to preserve diagnostic quality, it may result in side effects and may affect the radiotracer’s biodistribution. This study aims to investigate the feasibility of sedation-free pediatric PET imaging using ultra-fast total-body (TB) PET scanners and deep learning (DL)-based attenuation and scatter correction (ASC).This retrospective study included TB PET (uExplorer) imaging of 35 sedated pediatric patients under four years old to determine the minimum effective scanning time. A DL-based ASC method was applied to enhance PET quantification. Both quantitative and qualitative assessments were conducted to evaluate the image quality of ultra-fast DL-ASC PET. Five non-sedated pediatric patients were subsequently used to validate the proposed approach.Comparisons between standard 300-second and ultra-fast 15-second imaging, CT-ASC and DL-ASC ultra-fast 15-second images, as well as DL-ASC ultra-fast 15-second images in non-sedated and sedated patients, showed no significant differences in qualitative scoring, lesion detectability, and quantitative Standard Uptake Value (SUV) (P = ns).This study demonstrates that pediatric PET imaging can be effectively performed without sedation by combining ultra-fast imaging techniques with a DL-based ASC. This advancement in sedation-free ultra-fast PET imaging holds potential for broader clinical adoption.Methods: While sedation is routinely used in pediatric PET examinations to preserve diagnostic quality, it may result in side effects and may affect the radiotracer’s biodistribution. This study aims to investigate the feasibility of sedation-free pediatric PET imaging using ultra-fast total-body (TB) PET scanners and deep learning (DL)-based attenuation and scatter correction (ASC).This retrospective study included TB PET (uExplorer) imaging of 35 sedated pediatric patients under four years old to determine the minimum effective scanning time. A DL-based ASC method was applied to enhance PET quantification. Both quantitative and qualitative assessments were conducted to evaluate the image quality of ultra-fast DL-ASC PET. Five non-sedated pediatric patients were subsequently used to validate the proposed approach.Comparisons between standard 300-second and ultra-fast 15-second imaging, CT-ASC and DL-ASC ultra-fast 15-second images, as well as DL-ASC ultra-fast 15-second images in non-sedated and sedated patients, showed no significant differences in qualitative scoring, lesion detectability, and quantitative Standard Uptake Value (SUV) (P = ns).This study demonstrates that pediatric PET imaging can be effectively performed without sedation by combining ultra-fast imaging techniques with a DL-based ASC. This advancement in sedation-free ultra-fast PET imaging holds potential for broader clinical adoption.Results: While sedation is routinely used in pediatric PET examinations to preserve diagnostic quality, it may result in side effects and may affect the radiotracer’s biodistribution. This study aims to investigate the feasibility of sedation-free pediatric PET imaging using ultra-fast total-body (TB) PET scanners and deep learning (DL)-based attenuation and scatter correction (ASC).This retrospective study included TB PET (uExplorer) imaging of 35 sedated pediatric patients under four years old to determine the minimum effective scanning time. A DL-based ASC method was applied to enhance PET quantification. Both quantitative and qualitative assessments were conducted to evaluate the image quality of ultra-fast DL-ASC PET. Five non-sedated pediatric patients were subsequently used to validate the proposed approach.Comparisons between standard 300-second and ultra-fast 15-second imaging, CT-ASC and DL-ASC ultra-fast 15-second images, as well as DL-ASC ultra-fast 15-second images in non-sedated and sedated patients, showed no significant differences in qualitative scoring, lesion detectability, and quantitative Standard Uptake Value (SUV) (P = ns).This study demonstrates that pediatric PET imaging can be effectively performed without sedation by combining ultra-fast imaging techniques with a DL-based ASC. This advancement in sedation-free ultra-fast PET imaging holds potential for broader clinical adoption.Conclusions: While sedation is routinely used in pediatric PET examinations to preserve diagnostic quality, it may result in side effects and may affect the radiotracer’s biodistribution. This study aims to investigate the feasibility of sedation-free pediatric PET imaging using ultra-fast total-body (TB) PET scanners and deep learning (DL)-based attenuation and scatter correction (ASC).This retrospective study included TB PET (uExplorer) imaging of 35 sedated pediatric patients under four years old to determine the minimum effective scanning time. A DL-based ASC method was applied to enhance PET quantification. Both quantitative and qualitative assessments were conducted to evaluate the image quality of ultra-fast DL-ASC PET. Five non-sedated pediatric patients were subsequently used to validate the proposed approach.Comparisons between standard 300-second and ultra-fast 15-second imaging, CT-ASC and DL-ASC ultra-fast 15-second images, as well as DL-ASC ultra-fast 15-second images in non-sedated and sedated patients, showed no significant differences in qualitative scoring, lesion detectability, and quantitative Standard Uptake Value (SUV) (P = ns).This study demonstrates that pediatric PET imaging can be effectively performed without sedation by combining ultra-fast imaging techniques with a DL-based ASC. This advancement in sedation-free ultra-fast PET imaging holds potential for broader clinical adoption. [ABSTRACT FROM AUTHOR]

Seismic data acquired in seismic exploration is often contaminated by random noise, and it is necessary to develop effective seismic data denoising methods in seismic signal processing. The current seismic data denoising solutions mainly include traditional model-based methods and supervised deep learning methods. However, the traditional model-based methods cannot achieve satisfactory denoising accuracy, while the supervised deep learning methods have a demand for labeled data, which is difficult to collect in field seismic exploration. To address these difficulties in seismic signal denoising, we proposed an unsupervised deep learning method USDDM (Unsupervised Seismic Denoising Diffusion Model) based on diffusion model. USDDM utilizes the forward process of a diffusion model to assimilate the noise in seismic data, and then the backward process of the diffusion model is used to gradually remove the assimilated noise. Experiments on synthetic and field data are carried out to evaluate the denoising performance of USDDM, model-based methods f-x deconvolution and curvelet, and supervised deep learning methods CAE and DnCNN are used as comparison models. The results of the simulated experiments suggest that the proposed USDDM can effectively reduce the random noise in contaminated seismic data. USDDM can achieve better denoising accuracy compared to f-x deconvolution and curvelet, and the performance between USDDM and supervised deep learning methods is very close. The effectiveness and practicality of USDDM are demonstrated. [ABSTRACT FROM AUTHOR]

Background and objective: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET.23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map.Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach.Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.Methods: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET.23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map.Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach.Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.Results: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET.23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map.Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach.Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.Conclusion: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET.23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map.Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach.Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map. [ABSTRACT FROM AUTHOR]

Purpose: A critical bottleneck for the credibility of artificial intelligence (AI) is replicating the results in the diversity of clinical practice. We aimed to develop an AI that can be independently applied to recover high-quality imaging from low-dose scans on different scanners and tracers. Methods: Brain [18F]FDG PET imaging of 237 patients scanned with one scanner was used for the development of AI technology. The developed algorithm was then tested on [18F]FDG PET images of 45 patients scanned with three different scanners, [18F]FET PET images of 18 patients scanned with two different scanners, as well as [18F]Florbetapir images of 10 patients. A conditional generative adversarial network (GAN) was customized for cross-scanner and cross-tracer optimization. Three nuclear medicine physicians independently assessed the utility of the results in a clinical setting. Results: The improvement achieved by AI recovery significantly correlated with the baseline image quality indicated by structural similarity index measurement (SSIM) (r = −0.71, p < 0.05) and normalized dose acquisition (r = −0.60, p < 0.05). Our cross-scanner and cross-tracer AI methodology showed utility based on both physical and clinical image assessment (p < 0.05). Conclusion: The deep learning development for extensible application on unknown scanners and tracers may improve the trustworthiness and clinical acceptability of AI-based dose reduction. [ABSTRACT FROM AUTHOR]

Two new metal-organic compounds, namely [Cu(CrO4)(4,4'-bipy)(H2O)]·n(H2O) (1) together with [Mn(Cr2O7)(bpp)2]n (2) (4,4'-bipy is 4,4'-bipyridine and bpp is 1,3-bis(4-pyridyl)propane), were hydrothermally generated, which were characterized structurally through a series of characterization techniques. Moreover, compounds 1 and 2 have 2.95 eV and 3.02 eV of narrow optical band gap values, and possess outstanding photocatalytic effects for the methylene blue degradation under irradiation of visible light. The application of above compounds in the ophthalmic local anesthesia was examined and the specific mechanism was tested. First of all, the acetylcholine content in the synaptic cleft was measured with enzyme linked immunosorbent assay (ELISA) assay after treated with the CPs. The acetylcholine receptor relative expression on nerve cells was subsequently measured via real time reverse transcription-polymerase chain reaction (RT-PCR) under the treatment of compounds. In the end, the complexes' toxicity was evaluated by Cell Counting Kit-8 (CCK-8) detection. [ABSTRACT FROM AUTHOR]

Non-maximum suppression (NMS) is a post-processing step in most object detection pipelines. It is a greedy algorithm based on the Intersection over Union (IoU) of the bounding boxes to reduce false positives by removing excessive repeated bounding boxes, yet the geometric distributions of bounding boxes are not fully utilized. It is found that the distributions of bounding boxes' center points correspond to the distributions of objects. Local areas with clustered distributions of center points exist objects. Local areas with sparse distributions of center points are considered as the false positives or noises of the detector. In this work, a density-based NMS (DB-NMS) is proposed, which is based on the density distributions of the bounding boxes' center points to evaluate the importance of difference anchors. The proposed DB-NMS is able to obtain better results than the original NMS on the MS-COCO 2017 dataset. Because DB-NMS does not change the network structure, it can be easily integrated into the object detection pipelines to achieve better performances. Object detection pipelines such as Faster R-CNN and RetinaNet can be integrated with the proposed DB-NMS with little degradation on the computational efficiency. [ABSTRACT FROM AUTHOR]

In recent years, transformers have become a significant tool in computer vision, revolutionizing fundamental tasks. This paper focuses on the mapping strategy employed during patch embedding, explicitly addressing the transition from a two-dimensional (2D) to a one-dimensional (1D) representation. Existing methods typically divide images into tokens and perform sequential mapping in a top-to-bottom, left-to-right manner. However, these approaches suffer from a notable loss of local information due to the inherent discontinuity in the mapping process. To address these limitations, we propose a novel solution called Geometric-Fractals-based Position Encoding for Vision Transformer (GFPE-ViT). Our method capitalizes on the self-similarity and periodicity observed in fractal curves to enhance the proximity of local information. By integrating the fractalized order into the position encoding, considering the fractal periodicity, we effectively improve the simplicity and efficacy of the mapping strategy. Extensive experimental evaluations highlight the superiority of our approach over existing methods. GFPE-ViT achieves higher accuracy and faster convergence, underscoring its effectiveness in enhancing the mapping strategy for image patching tasks. Results show that GFPE-ViT performs 0.38% higher than the vanilla ViT in terms of top-1 accuracy on CIFAR-100 after pre-training with ImageNet-21k and achieves a 50% reduction in convergence time compared to vanilla ViT on small-scale datasets. By leveraging the self-similarity and periodicity in fractal curves, our proposed method opens new avenues for improving local information proximity in computer vision tasks. [ABSTRACT FROM AUTHOR]

Premature failure of the spring diaphragm of coupling in wind power generator has been frequently reported. The cause of the failure spring diaphragm was analyzed by chemical composition, mechanical property, and microstructure morphology. The results showed that the fatigue failure mode initiated on the surface of the spring diaphragm resulting from cyclic loading conditions during operation. The fatigue was the main reason for failure of the spring diaphragm. The micro-crack was initiated on the spring diaphragm due to the slightly loosed and the cyclic bending fatigue. Meanwhile, the brittleness was increased, and the resist ability of crack was reduced due to the overtop yield strength ratio. Therefore, the micro-crack was extended until the spring diaphragm was broken on the combined action of fatigue and the material's high yield strength ratio. Suggestions to prevent the similar failure were proposed based on the analysis results. [ABSTRACT FROM AUTHOR]

Let G = (V , E) be a graph. A subset S ⊆ V is a 2-dominating set of G if each vertex in V - S is adjacent to at least two vertices in S. The 2-domination number of G is the cardinality of the smallest 2-dominating set of G. In this paper, we shall prove that the 2-domination number of generalized Petersen graphs P (5 k + 1 , 3) , P (5 k + 2 , 3) and P (5 k + 3 , 3) is 4 k + 2 , 4 k + 3 and 4 k + 4 , respectively. This proves one conjecture due to Bakhshesh et al. (Proc. Indian Acad. Sci. (Math. Sci.)128 (2018) 17). [ABSTRACT FROM AUTHOR]

Pseudomonas stutzeri strain XL-2 exhibited significant performance on biofilm formation. Extracellular polymeric substances (EPS) secreted by strain XL-2 were characterized by colorimetry and Fourier transform infrared (FT-IR) spectroscopy. The biofilm growth showed a strong positive correlation (rP=0.96, P<0.01) to extracellular protein content, but no correlation to exopolysaccharide content. Hydrolyzing the biofilm with proteinase K caused a significant decrease in biofilm growth (t=3.7, P<0.05), whereas the changes in biofilm growth were not significant when the biofilm was hydrolyzed by α-amylase and β-amylase, implying that proteins rather than polysaccharides played the dominant role in biofilm formation. More specifically, confocal laser scanning microscopy (CLSM) revealed that the extracellular proteins were tightly bound to the cells, resulting in the cells with EPS presenting more biofilm promotion protein secondary structures, such as three-turn helices, β-sheet, and α-helices, than cells without EPS. Both bio-assays and quantitative analysis demonstrated that strain XL-2 produced signal molecules of N-acylhomoserine lactones (AHLs) during biofilm formation process. The concentrations of C6-HLS and C6-oxo-HLS were both significantly positively correlated with protein contents (P<0.05). Dosing exogenous C6-HLS and C6-oxo-HLS also resulted in the increase in protein content. Therefore, it was speculated that C6-HLS and C6-oxo-HLS released by strain XL-2 could up-regulate the secretion of proteins in EPS, and thus promote the formation of biofilm. [ABSTRACT FROM AUTHOR]

Object recognition in complex backgrounds has challenged the fields of pattern recognition for years. It is even harder when the targets in images are of different poses. Current methods use descriptors of characteristic vectors and machine learning algorithms to produce classifiers for object recognition. However, the generalization ability of these methods relies on the quality of the training phase and cannot find the precise boundaries of the targets. The geometric features of objects are the most stable and consistent features, so the recognition method based on shapes can be more intuitive than those based on color and texture features. This paper proposes a novel method that uses the images represented by line segments. The recognition mission becomes to effectively filter and combine them. The contour fragments after combinations are expected to satisfy the given model, or certain parts of it. In this way, object recognition can be viewed as a combinatorial optimization problem. This paper develops a genetic algorithm-based method to solve this problem. The experimental results show that this method can solve the combinatorial optimization problem effectively and can accurately distinguish the contour of the target object from the background. This method, which is based on geometric features, may contribute to the development of explicit principals for the description of object structure and recognition method based on symbolic reasoning. [ABSTRACT FROM AUTHOR]

The cause of a longitudinal fracture of an automotive bushing during the assembly process is presented in this study. On the basis of macroscopic inspection, scanning electron microscopy, energy-dispersive spectroscopy, microstructural examination, chemical analysis and hardness measurements, cleavage fracture was determined by the dominant fracture mode, and the fracture near the outer surface of the bushing was covered by impurities which is similar to the composition of the coating. Therefore, it is possible to infer that the crack existed before installation. In addition, the detailed metallurgical analysis demonstrates decarburization at the fracture surface due to a folding defect. In the process of assembly of bushing, the stress concentration and surface defect promoted the old crack propagation, finally, leading to the fracture of the bushing. [ABSTRACT FROM AUTHOR]

Given that the radial-inflow turbine is a critical component of the Organic Rankine cycle system, its performance substantially influences system capacity. This paper established an optimization framework for the radial-inflow turbine is established with the combination of a computational fluid dynamics software, a non-uniform rational B-spline parameterization method, and an optimization strategy. The nozzle, meridional flow path, and blade profile of a 500 kW turbine were optimized. Results show that nozzle blade and impeller optimization leads to a 0.34 % and about 0.71 % increase in turbine efficiency, respectively. After optimization, the flow state in the turbine was good, and the flow separation almost disappeared. [ABSTRACT FROM AUTHOR]

Three different microstructures with line pattern, grid pattern, and spot pattern were fabricated on titanium surfaces by nanosecond laser. Scanning electron microscopy (SEM), contact angle measurement, surface roughness gage, and X-ray photoelectron spectroscopy (XPS) analyses were used to characterize and measure the surface morphology, contact angle, surface roughness, and chemical composition of titanium after laser processing. The results indicate that the contact angle of titanium surface is 77.8° immediately after laser processing, which shows hydrophilicity, and the contact angle presents a rising tendency with time in general. At steady state, the maximum contact angles for line pattern, grid pattern, and spot pattern increased to 157.2°, 153°, and 132.5°, respectively. It can be found that the surface wettability has changed from hydrophilicity to hydrophobicity and even to superhydrophobicity. The influence of surface morphology on the surface wettability effects immediately after laser treatment and does not change with time, while the effect of surface chemical composition on the surface wettability will continue from the beginning of laser processing to the stabilization of surface chemical composition. Finally, it can be deduced that the accumulation of carbon on the surface is probably the critical factor to improve the surface hydrophobicity. Therefore, it is concluded that laser-induced modification of surface wettability correlates with surface morphology and surface chemical composition. [ABSTRACT FROM AUTHOR]

Previous fMRI studies related to emotional conflict focused on task activation during the specific experimental paradigm. Yet, the underlying spontaneous neural activity was largely unknown. Here, this was the first study using resting-state fMRI to explore the spontaneous neural activity related to emotional conflict. We used the whole-brain analysis to investigate the association between emotional conflict and amplitude of low-frequency fluctuations (ALFF) in a large sample. We found that the emotional conflict effect was negatively correlated with ALFF in the right AMY. These findings implied that AMY was the key region which plays a crucial role in emotional conflict. [ABSTRACT FROM AUTHOR]

Eyes absent (Eya) is a highly conserved transcription cofactor and protein phosphatase that regulates multiple developmental processes throughout the metazoans. It is a dual function protein, working as a transcription factor in the nucleus and as a tyrosine phosphatase in the cytoplasm. In this study, we isolated EYA-1 of Caenorhabditis elegans, the only homolog of Eyes absent, and set up an effective feeding-based RNAi (RNA interference) against the gene. We found that knockdown of EYA-1 decreased heat and oxidative stress tolerance and accelerated the onset of paralysis mediated by Aβ1-42 proteotoxicity and polyQ. Under heat stress (35°C), EYA-1 knockdown shortened the mean lifespan by 16.8%, which could be attributed to decrease in heat shock protein-16.2 ( hsp-16.2) expression. Under oxidative stress, EYA-1 knockdown could shorten the mean lifespan by 18.7%, which could be attributed to intracellular ROS accumulation and the decrease of superoxide dismutase-3 ( sod-3) protein expression. Moreover, EYA-1 knockdown animals also showed increased lipofuscin accumulation under oxidative stress. Further studies demonstrated that EYA-1 knockdown could not inhibit daf-16 nuclear accumulation in wild-type worms in response to stress. On the other hand, EYA-1 deficiency did not further reduce stress resistance of daf-16 mutants, which are stress sensitive. Quantitative real-time PCR results also showed that the expression of two daf-16 target genes, hsp-12.3 and sod-3, was downregulated in EYA-1 RNAi-treated worms under stress. All this evidence indicates EYA-1 is required for stress resistance of worms, and it might act downstream of daf-16 to regulate expression of stress resistance-associated genes. [ABSTRACT FROM AUTHOR]

Outbreaks of mass mortalities among cultured megalopa of swimming crab ( Portunus trituberculatus) occurred in a commercial hatchery during the spring of 2012 in Jiangsu province, P. R. China. Dominant bacteria were isolated and characterized by biochemical reactions, enzyme production, and sequencing analysis of the 16S rRNA, gyrB (DNA gyrase B subunit) genes, and two strains (DY1 and DY2) were selected as representative strains for virulence tests by immersion. The results showed that the characteristics of identified strains consist with Vibrio harveyi; the 16S rRNA and gyrB genes of the tested strains exhibited high similarity with V. harveyi; and the phylogenetic trees constructed using the neighbor-joining method based on 16S rRNA and gyrB genes. Two strains (DY1 and DY2) clustered with the V. harveyi and were supported by a higher bootstrap value, and two strains (DY1 and DY2) were found lethal to the healthy megalopa and juvenile crab. LD of DY1 and DY2 to megalopa and juvenile crab were 2.4 × 10, 3.0 × 10, 1.9 × 10 and 2.5 × 10 CFU/ml, respectively. The results confirmed that the diseased megalopa were infected by V. harveyi. In addition, we analyzed the tested strains (DY1 and DY2) by PCR for the presence of virulence genes that were known in V. harveyi, and the results showed that five virulence genes (luxR, toxR, vhhA, vhhB and pap6) were detected by a specific PCR assay, further supporting the assignment of isolates to V. harveyi and its pathogenicity. To our knowledge, this is the first report of V. harveyi as pathogenic bacteria of megalopa of swimming crab. [ABSTRACT FROM AUTHOR]

In this article, the influences of temperature and atmosphere on thermal stability of BaCrO were investigated. BaCrO powders with an orthorhombic structure were synthesized by a facile aqueous solution route. The synthesized BaCrO products were then heat treated at different atmospheres to evaluate their thermal stability by differential thermal analysis-thermogravimetry (DTA-TG), X-ray photoelectron spectroscopy and X-ray diffraction. BaCrO has a good thermal stability and does not decompose in air up to 1,400 °C. However, the decomposition of BaCrO in vacuum depends mainly upon a two-stage chemical reaction. BaCrO is finally decomposed into BaCrO with trivalent Cr cations and Ba(Cr Cr)O with both pentavalent Cr and hexavalent Cr cations after heat treatments in vacuum. [ABSTRACT FROM AUTHOR]

Osteoporosis (OP) has been associated with cardiovascular disease. More specifically, osteoporosis was found to be an independent predictor of cardiovascular mortality. Recent studies revealed that platelets play a critical role in bone remodeling. Mean platelet volume (MPV) is an early marker of platelet activation, which is involved in the pathophysiology of coronary heart disease. However, little research has been conducted to investigate the relationship between MPV and OP. In this cross-sectional study, we investigated the relationship between platelet count, MPV, and bone mineral density (BMD) in 410 subjects in the geriatric department of the Second Affiliated Hospital, Harbin, China. Different biochemical parameters, platelet count, and MPV were determined, and bone mineral density (BMD) (g/cm) was measured in the osteoporosis, osteopenia, and normal BMD groups. Mean age, systolic blood pressure (SBP), total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C), fasting plasma glucose (FPG), and MPV increased gradually, and body mass index (BMI), decreased as BMD decreased. A negative correlation was present between MPV and the lumbar spine (L2-L4) and femoral neck BMD after adjusting other risk factors. Univariate analysis and multivariate analysis showed that MPV was significantly associated with lumbar spine L2-L4 BMD and femoral neck BMD (β = −0.285, P < 0.001 for lumbar spine L2-L4 BMD; β = −0.207, P < 0.001 for femoral neck BMD in multivariate model). The findings show that MPV is negatively correlated with BMD. Further studies on the involvement of MPV in osteoporosis may contribute to the evaluation of thrombotic risk in elderly patients with osteoporosis. [ABSTRACT FROM AUTHOR]

Background and Objective: No study has been published that compared persistence and discontinuation of warfarin with other long-term medications in patients with atrial fibrillation (AF). The objective of this study was to evaluate persistence and discontinuation patterns in AF patients taking warfarin and other common long-term medications and identify predictors of persistence and discontinuation in this population. Methods: Patients with warfarin prescription within 3 months after AF hospitalization discharge and 12-month data before and after the first prescription were evaluated using administrative claims data (1 January 2005 - 31 December 2007). For comparison, persistence patterns for other long-term medications for treatment of hypertension, hyperglycemia, heart disease, and dyslipidemia, including once- (od) and twice- (bid) daily medications, were evaluated. Non-persistence was defined as the presence of a ≥60-day gap in medication use. Permanent discontinuation was defined as no use of the medication for ≥90 days until the end of the follow-up period. Multivariate analysis was conducted to identify predictors of warfarin non-persistence and discontinuation. Results: 28 384 patients with AF were identified; 16 036 (56.5%) had a warfarin prescription following AF hospitalization. 53.5 % of warfarin users were persistent for at least 1 year, similar to other long-term medications commonly prescribed to the AF population (ranging between 45.2% and 61.3 %). 42.6 % of warfarin users permanently discontinued warfarin within 1 year, also consistent with the discontinuation rate of 32.9-52.0% of other long-term medications. Residence in the South and West regions of the US, history of cardiac dysrhythmias, and warfarin cost-sharing significantly decreased the likelihood of warfarin persistence and increased the likelihood of discontinuation, while older age, history of ischemic stroke, and warfarin use before hospitalization significantly increased warfarin persistence and decreased the likelihood of discontinuation. Adherence of od and bid medications was similar. Conclusion: Persistence and discontinuation with warfarin in patients with AF is consistent with other long-term medications. Identifying factors associated with non-persistence and discontinuation with long-term medications can help in developing targeted adherence programs. [ABSTRACT FROM AUTHOR]

In this article, friction and wear characteristics of BaCrO ceramics have been investigated using a high-temperature friction and wear tester from room temperature to 800 °C in dry sliding against sintered alumina ball. At room temperature, the friction coefficient and wear rate of BaCrO ceramics are quite high. BaCrO ceramics exhibit low friction coefficients and small wear rates with temperature increasing up to 400-600 °C. The oxidation reaction of BaCrO during high-temperature wear tests is responsible for the tribological properties. The oxidized product of BaCrO is BaCrO, which forms a smooth self-lubricating film on the worn surface to effectively reduce friction and wear. However, at 800 °C, severe oxidation reduces the relative density of sintered BaCrO ceramics, and further expedites the materials removal process. [ABSTRACT FROM AUTHOR]

Investigations on the EtOH extract of Cucumis sativus roots led to the isolation of 15 compounds ( 1-15). Their structures were identified using spectroscopic methods. Among these compounds, compound 1, stigmasta-8(14),22-diene-7α-methoxy-3β-ol, is a new steroid, and 2, 4-15 were isolated from this plant for the first time. [ABSTRACT FROM AUTHOR]

A new end-to-end thiocyanato-bridged 1D polymeric copper(II) complex [CuL( μ-NCS)] ( 1), and a new end-on azido-bridged dimeric copper(II) complex [CuBrL( μ-N)] ( 2), where L is the deprotonated form of 2-[1-(2-methylaminoethylimino)ethyl]phenol (HL) and L is N-methyl- N′-(1-pyridin-2-ylethylidene)ethane-1,2-diamine, have been synthesized and structurally characterized by elemental analysis, IR spectra, and single-crystal X-ray diffraction. Complex 1 crystallizes in the monoclinic space group P2/ n with unit cell dimensions a = 10.822(1) Å, b = 10.054(1) Å, c = 12.532(2) Å, β = 106.810(2)°, V = 1305.3(3) Å, Z = 4, R = 0.0341 and wR = 0.0766. Complex 2 crystallizes in the monoclinic space group P2/ n with unit cell dimensions a = 10.427(2) Å, b = 10.672(2) Å, c = 12.626(2) Å, β = 108.069(9)°, V = 1335.7(4) Å, Z = 2, R = 0.0346 and wR = 0.0714. The Cu atom in 1 is in a square pyramidal coordination, and that in 2 is in an octahedral coordination. The Cu···Cu distances are 6.406(1) Å in 1, and 3.762(1) Å in 2. The pseudohalide anions are versatile bridging groups for the construction of polymeric structures of Schiff base copper(II) complexes. Graphical Abstract: Two new polymeric copper(II) complexes derived from tridentate Schiff bases have been synthesized and characterized.[Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Purpose: Few studies have evaluated the growth pattern of renal cell carcinoma (RCC) in patients with delayed treatment. This report investigated the growth rate and stage progression of incidentally discovered RCC following a long period of active surveillance. Methods: Thirty-two patients who did not receive immediate surgical treatment for renal solid masses that later proved to be RCC were reviewed retrospectively. Annual tumor growth rates were calculated according to changes in the maximal diameter on CT or MRI. Clinical and pathological characteristics associated with tumor growth rate and stage progression were analyzed. Results: The median tumor size grow from 2.14 (range, 0.30-6.70) cm to 4.33 (range, 1.40-8.80) cm after a median 46.0 months observation period. The average tumor growth rate was 0.80 (range, 0.16-3.80) cm/year. Clear cell carcinoma (0.86 cm/year) tended to grow faster than papillary cell carcinoma (0.28 cm/year) ( P = 0.066). The mean growth rate of grade 2 tumors (0.88 cm/year) was faster than that of grade 1 tumors (0.36 cm/year) ( P = 0.041). Thirteen tumors (40.6%) were upstaged at a median 48 months after initial presentation. Cox regression analysis revealed initial tumor size as the only risk factor for upstaging ( P = 0.018). No local and systemic recurrences were noted in our cohort after the intervention at a median of 47 (range, 6-248) months of follow-up. Conclusions: RCCs were found to be slow growing in a group of untreated renal cell carcinoma patients. However, some tumors progressed in stage under observation. The growth rate of RCC tended to correlate with histologic grade and histologic subtype. [ABSTRACT FROM AUTHOR]

This paper is devoted to the strong convergence of two kinds of general viscosity iteration processes for approximating common fixed points of a nonexpansive semigroup in Hilbert spaces. The results presented in this paper improve and generalize some corresponding results in (X. Li et al., 2009, S. Li et al., 2009, and Marino and Xu, 2006). [ABSTRACT FROM AUTHOR]

Purpose: This study aims to develop deep learning techniques on total-body PET to bolster the feasibility of sedation-free pediatric PET imaging. Methods: A deformable 3D U-Net was developed based on 245 adult subjects with standard total-body PET imaging for the quality enhancement of simulated rapid imaging. The developed method was first tested on 16 children receiving total-body [18F]FDG PET scans with standard 300-s acquisition time with sedation. Sixteen rapid scans (acquisition time about 3 s, 6 s, 15 s, 30 s, and 75 s) were retrospectively simulated by selecting the reconstruction time window. In the end, the developed methodology was prospectively tested on five children without sedation to prove the routine feasibility. Results: The approach significantly improved the subjective image quality and lesion conspicuity in abdominal and pelvic regions of the generated 6-s data. In the first test set, the proposed method enhanced the objective image quality metrics of 6-s data, such as PSNR (from 29.13 to 37.09, p < 0.01) and SSIM (from 0.906 to 0.921, p < 0.01). Furthermore, the errors of mean standardized uptake values (SUVmean) for lesions between 300-s data and 6-s data were reduced from 12.9 to 4.1% (p < 0.01), and the errors of max SUV (SUVmax) were reduced from 17.4 to 6.2% (p < 0.01). In the prospective test, radiologists reached a high degree of consistency on the clinical feasibility of the enhanced PET images. Conclusion: The proposed method can effectively enhance the image quality of total-body PET scanning with ultrafast acquisition time, leading to meeting clinical diagnostic requirements of lesion detectability and quantification in abdominal and pelvic regions. It has much potential to solve the dilemma of the use of sedation and long acquisition time that influence the health of pediatric patients. [ABSTRACT FROM AUTHOR]

We study the strong convergence of two kinds of viscosity iteration processes for approximating common fixed points of the pseudocontractive semigroup in uniformly convex Banach spaces with uniformly Gâteaux differential norms. As special cases, we get the strong convergence of the implicit viscosity iteration process for approximating common fixed points of the nonexpansive semigroup in Banach spaces satisfying some conditions. The results presented in this paper extend and generalize some results concerned with the nonexpansive semigroup in (Chen and He, 2007) and the pseudocontractive mapping in (Zegeye et al., 2007) to the pseudocontractive semigroup in Banach spaces under different conditions. [ABSTRACT FROM AUTHOR]

We have shown that the quorum-sensing signals acylhomoserine lactones, autoinducer-2 (AI-2) and indole influence the biofilm formation of Escherichia coli. Here, we investigate how the environment, that is, temperature, affects indole and AI-2 signaling in E. coli. We show in biofilms that indole addition leads to more extensive differential gene expression at 30 °C (186 genes) than at 37 °C (59 genes), that indole reduces biofilm formation (without affecting growth) more significantly at 25 and 30 °C than at 37 °C and that the effect is associated with the quorum-sensing protein SdiA. The addition of indole at 30 °C compared to 37 °C most significantly repressed genes involved in uridine monophosphate (UMP) biosynthesis (carAB, pyrLBI, pyrC, pyrD, pyrF and upp) and uracil transport (uraA). These uracil-related genes are also repressed at 30 °C by SdiA, which confirms SdiA is involved in indole signaling. Also, compared to 37 °C, indole more significantly decreased flagella-related qseB, flhD and fliA promoter activity, enhanced antibiotic resistance and inhibited cell division at 30 °C. In contrast to indole and SdiA, the addition of (S)-4,5-dihydroxy-2,3-pentanedione (the AI-2 precursor) leads to more extensive differential gene expression at 37 °C (63 genes) than at 30 °C (11 genes), and, rather than repressing UMP synthesis genes, AI-2 induces them at 37 °C (but not at 30 °C). Also, the addition of AI-2 induces the transcription of virulence genes in enterohemorrhagic E. coli O157:H7 at 37 °C but not at 30 °C. Hence, cell signals cause diverse responses at different temperatures, and indole- and AI-2-based signaling are intertwined.The ISME Journal (2008) 2, 1007–1023; doi:10.1038/ismej.2008.54; published online 5 June 2008 [ABSTRACT FROM AUTHOR]

Quorum-sensing signal autoinducer 2 (AI-2) stimulates Escherichia coli biofilm formation through the motility regulator MqsR that induces expression of the putative transcription factor encoded by yncC. Here, we show that YncC increases biofilm formation by repressing overproduction of the exopolysaccharide identified as colanic acid (corroborated by decreasing mucoidy and increased sensitivity to bacteriophage P1 infection). Differential gene expression and gel shift assays demonstrated that YncC is a repressor of the predicted periplasmic protein-encoding gene, ybiM, which was corroborated by the isogenic yncC ybiM double mutation that repressed the yncC phenotypes (biofilm formation, colanic acid overproduction, mucoidy and bacteriophage resistance). Through nickel-enrichment DNA microarrays and additional gel shift assays, we found that the putative transcription factor B3023 (directly upstream of mqsR) binds the yncC promoter. Overexpressing MqsR, AI-2 import regulators LsrR/LsrK and AI-2 exporter TqsA induced yncC transcription, whereas the AI-2 synthase LuxS and B3023 repressed yncC. MqsR has a toxic effect on E. coli bacterial growth, which is partially reduced by the b3023 mutation. Therefore, AI-2 quorum-sensing control of biofilm formation is mediated through regulator MqsR that induces expression of the transcription factor YncC. YncC inhibits the expression of periplasmic YbiM, which prevents overproduction of colanic acid (excess colanic acid causes mucoidy) and prevents YbiM from inhibiting biofilm formation.The ISME Journal (2008) 2, 615–631; doi:10.1038/ismej.2008.24; published online 28 February 2008 [ABSTRACT FROM AUTHOR]

The general expressions of constitutive equations for isotropic elastic damaged materials were derived directly from the basic law of irreversible thermodynamics. The limitations of the classical damage constitutive equation based on the well-known strain equivalence hypothesis were overcome. The relationships between the two elastic isotropic damage models (i. e. single and double scalar damage models) were revealed. When a single scalar damage variable defined according to the microscopic geometry of a damaged material is used to describle the isotropic damage state, the constitutive equations contain two “damage effect functions”, which describe the different influences of damage on the two independent elastic constants. The classical damage constitutive equation based on the strain equivalence hypothesis is only the first-order approximation of the general expression. It may be unduly simplified and may fail to describe satisfactorily the damage phenomena of practical materials. [ABSTRACT FROM AUTHOR]

The general expressions of constitutive equations for isotropic elastic damaged materials were derived directly from the basic law of irreversible thermodynamics. The limitations of the classical damage constitutive equation based on the well-known strain equivalence hypothesis were overcome. The relationships between the two elastic isotropic damage models (i. e. single and double scalar damage models) were revealed. When a single scalar damage variable defined according to the microscopic geometry of a damaged material is used to describle the isotropic damage state, the constitutive equations contain two “damage effect functions”, which describe the different influences of damage on the two independent elastic constants. The classical damage constitutive equation based on the strain equivalence hypothesis is only the first-order approximation of the general expression. It may be unduly simplified and may fail to describe satisfactorily the damage phenomena of practical materials. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a chronic joint disorder that causes cartilage degradation and subchondral bone abnormalities. Nangibotide, also known as LR12, is a dodecapeptide with considerable anti-inflammatory properties, but its significance in OA is uncertain. The aim of the study was to determine whether nangibotide could attenuate the progression of OA, and elucidate the underlying mechanism. In vitro experiments showed that nangibotide strongly inhibited TNF-α-induced osteogenic reduction, significantly enhanced osteoblast proliferation and prevented apoptosis in MC3T3-E1 cells. Male C57BL/6 J mice aged 2 months were randomly allocated to three groups: sham, ACLT, and ACLT with nangibotide therapy. Nangibotide suppressed ACLT-induced cartilage degradation and MMP-13 expression. MicroCT analysis revealed that nangibotide attenuated in vivo subchondral bone loss induced by ACLT. Histomorphometry results showed that nangibotide attenuated ACLT-induced osteoblast inhibition; TUNEL assays and immunohistochemical staining of cleaved-caspase3 further confirmed the in vivo anti-apoptotic effect of nangibotide on osteoblasts. Furthermore, we found that nangibotide exerted protective effects by suppressing TGF-β signaling mediated by Smad2/3 to restore coupled bone remodeling in the subchondral bone. In conclusion, the findings suggest that nangibotide might exert a protective effect on the bone-cartilage unit and maybe an alternative treatment option for OA. [ABSTRACT FROM AUTHOR]

To improve the precision of defect categorization and localization in images, this paper proposes an approach for detecting surface defects in hot-rolled steel strips. The approach uses an improved YOLOv5 network model to overcome the issues of inadequate feature extraction capacity and suboptimal feature integration when identifying surface defects on steel strips. The proposed method achieves higher detection accuracy and localization precision, making it more competitive and applicable in real production. Firstly, the multi-scale feature fusion (MSF) strategy is utilized to fuse shallow and deep features effectively and enrich detailed information relevant to target defects. Secondly, the CSPLayer Res2Attention block (CRA block) residual module is introduced to reduce the loss of defect information during hierarchical transmission, thereby enhancing the extraction of fine-grained features and improving the perception of details and global features. Finally, the experimental results indicate that the mAP on the NEU-DET and GC10-DET datasets approaches 78.5% and 67.3%, respectively, which is 4.9% and 2.1% higher than that of the baseline. Meanwhile, it has higher precision and more precise localization capabilities than other methods. Furthermore, it also achieves 59.2% mAP on the APDDD dataset, indicating its potential for growth in further domains. [ABSTRACT FROM AUTHOR]

The laboratory plays a crucial role in science education. However, teacher education for pre-service teachers' design performance in the laboratory is still challenging. This study paved the way for redesigning traditional laboratory teaching into a student-centered approach: inquiry-based design thinking (IBDT). To investigate the impact of the IBDT approach on students' design performance of science experiments, 25 pre-service science teachers participated in a series of laboratory activities guided by the IBDT approach in a teacher education program in this study. Mixed research methods were employed to collect and analyze students' responses to pre- and post-surveys, their designed artifacts, and self-reflection reports. The overall positive results were obtained except for students' performance in art design, organization of the materials, and the gap between students' understanding of theories and their practices/practical skills. The findings will inform the laboratory instruction in teacher education in science or science-oriented Science-Technology-Engineering-Mathematics (STEM) education. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to establish an effective nomogram to predict primary distant metastasis (DM) in patients with nasopharyngeal carcinoma (NPC) to guide the application of PET/CT. Methods: In total, 3591 patients with pathologically confirmed NPC were consecutively enrolled. The nomogram was constructed based on 1922 patients treated between 2007 and 2014. Multivariate logistical regression was applied to identify the independent risk factors of DM. The predictive value of the nomogram was evaluated using the concordance index (C-index), calibration curve, probability density functions (PDFs), and clinical utility curve (CUC). The results were validated in 1669 patients enrolled from 2015 to 2016. Net reclassification improvement (NRI) was applied to compare performances of the nomogram with other clinical factors. The best cut-off value of the nomogram chosen for clinical application was analyzed. Results: A total of 355 patients showed primary DM among 3591 patients, yielding an incidence rate of 9.9%. Sex, N stage, EBV DNA level, lactate dehydrogenase level, and hemoglobin level were independent predictive factors for primary DM. C-indices in the training and validation cohort were 0.796 (95% CI, 0.76–0.83) and 0.779 (95% CI, 0.74–0.81), respectively. The NRI indices demonstrated that this model had better predictive performance than plasma EBV DNA level and N stage. We advocate for a threshold probability of 3.5% for guiding the application of PET/CT depending on the clinical utility analyses. Conclusion: This nomogram is a useful tool to predict primary DM of NPC and guide the clinical application of PET/CT individually at the initial staging. [ABSTRACT FROM AUTHOR]

Objectives: The value of using PET/CT for staging of stage I–II NPC remains unclear. Hence, we aimed to investigate the survival benefit of PET/CT for staging of early-stage NPC before radical therapy. Methods: A total of 1003 patients with pathologically confirmed NPC of stages I–II were consecutively enrolled. Among them, 218 patients underwent both PET/CT and conventional workup ([CWU], head-and-neck MRI, chest radiograph, liver ultrasound, bone scintigraphy) before treatment. The remaining 785 patients only underwent CWU. The standard of truth (SOT) for lymph node metastasis was defined by the change of size according to follow-up MRI. The diagnostic efficacies were compared in 218 patients who underwent both PET/CT and CWU. After covariate adjustment using propensity scoring, a cohort of 872 patients (218 with and 654 without pre-treatment PET/CT) was included. The primary outcome was overall survival based on intention to treat. Results: Retropharyngeal lymph nodes were metastatic based on follow-up MRI in 79 cases. PET/CT was significantly less sensitive than MRI in detecting retropharyngeal lymph node lesions (72.2% [62.3–82.1] vs. 91.1% [84.8–97.4], p = 0.004). Neck lymph nodes were metastatic in 89 cases and PET/CT was more sensitive than MRI (96.6% [92.8–100.0] vs. 76.4% [67.6–85.2], p < 0.001). In the survival analyses, there was no association between pre-treatment PET/CT use and improved overall survival, progression-free survival, local relapse-free survival, regional relapse-free survival, and distant metastasis-free survival. Conclusions: This study showed PET/CT is of little value for staging of stage I–II NPC patients at initial imaging. Key Points: • PET/CT was more sensitive than MRI in detecting neck lymph node lesions whereas it was significantly less sensitive than MRI in detecting retropharyngeal lymph node lesions. • No association existed between pre-treatment PET/CT use and improved survival in stage I–II NPC patients. [ABSTRACT FROM AUTHOR]

Benzoic acid decarboxylases offer an elegant alternative to CO2 fixation by reverse reaction-carboxylation, which is named the bio-Kolbe–Schmitt reaction, but they are unfavorable to carboxylation. Enhancing the carboxylation efficiency of reversible benzoic acid decarboxylases is restricted by the unexplained carboxylation mechanisms. The direction of reversible enzyme catalytic reactions depends on whether catalytic residues at the active center of the enzyme are protonated, which is subjected by the pH. Therefore, the forward and reverse reactions could be separated at different pH values. Reversible 2,3-dihydroxybenzoate acid decarboxylase undergoes decarboxylation at pH 5.0 and carboxylation at pH 8.6. However, it is unknown whether the interaction of enzymes with substrates and products in the forward and reverse reactions can be exploited to improve the catalytic activity of reversible enzymes in the unfavorable direction. Here, we identify a V-shaped tunnel of 2,3-dihydroxybenzoic acid decarboxylase from Aspergillus oryzae (2,3-DHBD_Ao) through which the substrate travels in the enzyme, and demonstrate that the side chain conformation of a tyrosine residue controls the entry and exit of substrate/product during reversible reactions. Together with the kinetic studies of the mutants, it is clarified that interactions between substrate/product traveling through the enzyme tunnel in 2,3-DHBD_Ao are direction-dependent. These results enrich the understanding of the interactions of substrates/products with macromolecular reversible enzymes in different reaction directions, thereby demonstrating a possible path for engineering decarboxylases with higher carboxylation efficiency. Key points: • The residue Trp23 of 2,3-DHBD_Ao served as a switch to control the entry and exit of catechol • A V-shaped tunnel of 2,3-DHBD_Ao for decarboxylation and carboxylation reactions was identified • The results provide a promising strategy for engineering decarboxylases with direction-dependent residues inside the substrate/product traveling tunnel of the enzyme [ABSTRACT FROM AUTHOR]

The production of American ginseng (Panax quinquefolius L.) is severely limited by the replant disorders in China. Crop rotation with maize might reduce the replant problems, but little information is available on the effect of maize rotation on soil cultivated with ginseng. In this study, we analyzed nutrients, phenolic acids, and microbial communities in soils from the fields with continuous maize, mono-culture ginseng, and 1-, 3-, and 5-year maize rotation after ginseng. Pot experiments were also conducted to evaluate the performance of replanting ginseng in these soils. The results showed that Mn, Cu, and 5 phenolic acids in ginseng-cultivated soil were significantly decreased by maize rotation. A 5-year maize rotation significantly increased the relative abundance of beneficial soil bacteria, such as Arthrobacter, rather than decreasing the abundances of potential pathogenic genera. Clustering analysis revealed that the physicochemical properties and microbial communities of 3- and 5-year maize rotation soil were more similar to CM than to G soil. The biomass of replanted ginseng root was improved, and root disease was reduced over 3 years of maize rotation. Overall, the results showed that at least a 3-year maize rotation is needed to overcome the replant failure of American ginseng. [ABSTRACT FROM AUTHOR]

Purpose: Long axial field-of-view (LAFOV) systems have a much higher sensitivity than standard axial field-of-view (SAFOV) PET systems for imaging the torso or full body, which allows faster and/or lower dose imaging. Despite its very high sensitivity, current total-body PET (TB-PET) throughput is limited by patient handling (positioning on the bed) and often a shortage of available personnel. This factor, combined with high system costs, makes it hard to justify the implementation of these systems for many academic and nearly all routine nuclear medicine departments. We, therefore, propose a novel, cost-effective, dual flat panel TB-PET system for patients in upright standing positions to avoid the time-consuming positioning on a PET-CT table; the walk-through (WT) TB-PET. We describe a patient-centered, flat panel PET design that offers very efficient patient throughput and uses monolithic detectors (with BGO or LYSO) with depth-of-interaction (DOI) capabilities and high intrinsic spatial resolution. We compare system sensitivity, component costs, and patient throughput of the proposed WT-TB-PET to a SAFOV (= 26 cm) and a LAFOV (= 106 cm) LSO PET systems. Methods: Patient width, height (= top head to start of thighs) and depth (= distance from the bed to front of patient) were derived from 40 randomly selected PET-CT scans to define the design dimensions of the WT-TB-PET. We compare this new PET system to the commercially available Siemens Biograph Vision 600 (SAFOV) and Siemens Quadra (LAFOV) PET-CT in terms of component costs, system sensitivity, and patient throughput. System cost comparison was based on estimating the cost of the two main components in the PET system (Silicon Photomultipliers (SiPMs) and scintillators). Sensitivity values were determined using Gate Monte Carlo simulations. Patient throughput times (including CT and scout scan, patient positioning on bed and transfer) were recorded for 1 day on a Siemens Vision 600 PET. These timing values were then used to estimate the expected patient throughput (assuming an equal patient radiotracer injected activity to patients and considering differences in system sensitivity and time-of-flight information) for WT-TB-PET, SAFOV and LAFOV PET. Results: The WT-TB-PET is composed of two flat panels; each is 70 cm wide and 106 cm high, with a 50-cm gap between both panels. These design dimensions were justified by the patient sizes measured from the 40 random PET-CT scans. Each panel consists of 14 × 20 monolithic BGO detector blocks that are 50 × 50 × 16 mm in size and are coupled to a readout with 6 × 6 mm SiPMs arrays. For the WT-TB-PET, the detector surface is reduced by a factor of 1.9 and the scintillator volume by a factor of 2.2 compared to LAFOV PET systems, while demonstrating comparable sensitivity and much better uniform spatial resolution (< 2 mm in all directions over the FOV). The estimated component cost for the WT-TB-PET is 3.3 × lower than that of a 106 cm LAFOV system and only 20% higher than the PET component costs of a SAFOV. The estimated maximum number of patients scanned on a standard 8-h working day increases from 28 (for SAFOV) to 53–60 (for LAFOV in limited/full acceptance) to 87 (for the WT-TB-PET). By scanning faster (more patients), the amount of ordered activity per patient can be reduced drastically: the WT-TB-PET requires 66% less ordered activity per patient than a SAFOV. Conclusions: We propose a monolithic BGO or LYSO-based WT-TB-PET system with DOI measurements that departs from the classical patient positioning on a table and allows patients to stand upright between two flat panels. The WT-TB-PET system provides a solution to achieve a much lower cost TB-PET approaching the cost of a SAFOV system. High patient throughput is increased by fast patient positioning between two vertical flat panel detectors of high sensitivity. High spatial resolution (< 2 mm) uniform over the FOV is obtained by using capable monolithic scintillators. [ABSTRACT FROM AUTHOR]

Objectives: Entropy is a new late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR)–derived parameter that is independent of signal intensity thresholds. Entropy can be used to measure myocardial tissue heterogeneity by comparing full pixel points of tissue images. This study investigated the incremental prognostic value of left ventricular (LV) entropy in patients with hypertrophic cardiomyopathy (HCM). Methods: This study enrolled 337 participants with HCM who underwent 3.0-T CMR. The LV entropy was obtained by calculating the probability distribution of the LV myocardial pixel signal intensities of the LGE sequence. Patients who underwent CMR imaging were followed up for endpoints. The primary endpoint was defined as readmission to the hospital owing to heart failure. The secondary endpoint was the composite of the primary endpoint, sudden cardiac death and non-cardiovascular death. Results: During the median follow-up of 24 months ± 13 (standard deviation), 43 patients who reached the primary and secondary endpoints had a higher entropy (6.20 ± 0.45, p < 0.001). The patients with increased entropy (≥ 5.587) had a higher risk of the primary and secondary endpoints, compared with HCM patients with low entropy (p < 0.001 for both). In addition, Cox analysis showed that LV entropy provided significant prognostic value for predicting both primary and secondary endpoints (HR: 1.291 and 1.273, all p < 0.001). Addition of LV entropy to the multivariable model improved model performance and risk reclassification (p < 0.05). Conclusion: LV entropy assessed by CMR was an independent predictor of primary and secondary endpoints. LV entropy assessment contributes to improved risk stratification in patients with HCM. Critical relevance statement: Myocardial heterogeneity reflected by entropy the derived parameter of LGE has prognostic value for adverse events in HCM. The measurement of LV entropy helped to identify patients with HCM who were at risk for heart failure and sudden cardiac death. Key points: • Left ventricular entropy can reflect myocardial heterogeneity in HCM patients. • Left ventricular entropy was significantly higher in HCM patients who reached endpoint events. • Left ventricular entropy helps to predict the occurrence of heart failure and death in HCM patients. [ABSTRACT FROM AUTHOR]

Natural disasters such as earthquakes have consecutive impacts on the smart grid because of aftershock activities. To guarantee service requirements and smart grid stable operations, it is a challenge to design a fast and survivable rerouting mechanism. There are few studies that consider concurrent rerouting aiming at multiple services in smart grid communication network, however. Firstly, we formulate the node survivability, link survivability, and path survivability model in terms of the distance from the epicenter to the node and the link of the network. Meanwhile, we introduce the indicator of site difference level which is unique in the smart grid to further restrict the service path. Secondly, to improve the algorithm efficiency and reduce rerouting time, the deep first search algorithm is utilized to obtain the available rerouting set, and then the I-DQN based on the framework of reinforcement learning is proposed to achieve concurrent rerouting for multiple services. The experimental results show that our approach has a better convergence performance and higher survivability as well as the approximate latency in comparison with other approaches. [ABSTRACT FROM AUTHOR]