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Bruton's tyrosine kinase (BTK) plays a crucial role in adaptive and immune responses by modulating B-cell, Fc, toll-like, and chemokine receptor signaling pathways. BTK inhibition is a promising therapeutic approach for the treatment of inflammatory and autoimmune diseases. The development of novel, highly selective, and less toxic BTK inhibitors may be beneficial for the treatment of autoimmune diseases with unmet medical needs. In this study, structure-based drug design was used to discover a series of novel, potent, and selective covalent BTK inhibitors with a 1,4,5,6,8-pentaazaacenaphthylen scaffold. Among them, compound 36R exhibited high kinase selectivity, long target occupancy time, appropriate pharmacokinetic properties, and dose-dependent efficacy in a rat model of collagen-induced arthritis. Therefore, 36R is a novel BTK inhibitor requiring further development for the treatment of autoimmune diseases.

The inertance hydraulic converter relies on fluid inertance to modulate flow or pressure and is considered to be a competitive alternative to the conventional proportional hydraulic system due to its potential advantage in efficiency. As the quantification of fluid inertance, the suction flow characteristic is the crucial performance indicator for efficiency improvement. To explore the discrepancy between the passive inertance hydraulic converter featured by the check valve and the active inertance hydraulic converter driven by an equivalent 2/3 way fast switching valve in regard to suction flow characteristics, analytical models of the inertance hydraulic converters were established in MATLAB/Simulink. The validated models of the respective suction components were incorporated in the overall analytical models and their suction flow characteristics were theoretically and experimentally discussed. The analytical predictions and experimental measurements for the current configurations indicated that the active inertance hydraulic converter yields a larger transient suction flow rate than that of the passive inertance hydraulic converter due to the difference of the respective suction components. The suction flow characteristic can be modulated using the supply pressure and duty cycle, which was confirmed by experimental measurements. In addition, the suction flow characteristics are heavily affected by the resistance of the suction flow passage and switching frequency. There is a compromise between the resistance and switching frequency for inertance hydraulic converters to achieve large suction flow rate.

In this paper, an electro-hydrostatic actuator driven by dual axial-mounted magnetostrictive material rods-based pumps (MMPs) with a new type of active rectification valve is designed in the current study. Based on flow distribution of the active rectification valve and driving energy provided by two MMPs, the actuator can output continuous and bidirectional displacement. By establishing a mathematical model of the actuating system, using simulation techniques, the change rule of hydraulic cylinder’s motion state caused by different driving signals are studied and analyzed. Test equipment platform is constructed in the laboratory to test the output characteristics and confirm the feasibility of the new concept. The experimental results indicate that the maximum flow rate can reach approximately 2.7 L·min−1, while the operating frequency is 180 Hz.

Pilot two-stage proportional valves are widely used in high-power hydraulic systems. For the purpose of improving the dynamic performance, reliability, and digitization of the traditional proportional valve, a novel two-stage proportional valve with a pilot digital flow distribution is proposed from the viewpoint of the dual nozzle-flapper valve’s working principle. In particular, the dual nozzle-flapper is decoupled by two high-speed on/off valves (HSVs). First, the working principle and mathematical model of the proposed valve are determined. Then, the influences of the control parameters (duty cycle and switching frequency) and structural parameters (fixed orifice’s diameter and main valve’s spring) on the main valve’s motion are analyzed on the basis of theory, simulation, and experiment. In addition, in optimizing the value of the fixed orifice’s diameter, a new design criterion that considers the maximum pressure sensitivity, flow controllability, and flow linearization is proposed to improve the balance between the effective displacement and the displacement fluctuation of the main valve. The new scheme is verified by simulations and experiments. Experimental results of the closed-loop displacement tracking have demonstrated that the delay time of the main valve is always within 3.5 ms under different working conditions, and the tracking error can be significantly reduced using the higher switching frequency. The amplitude-frequency experiments indicate that a − 3 dB-frequency of the proposed valve can reach 9.5 Hz in the case of ±50% full scale and 15 Hz in the case of 0%–50% full scale. The values can be further improved by increasing the flow rate of the pilot HSV.

This article focuses on accurate identification of the critical moving characteristics of the high speed on/off valve. Typically, there are two strategies for identifying the critical moving characteristics, including calculation strategy based on force balance and strategy for detecting the coil current’s certain points. However, the accuracy of the two above strategies needs to be improved. Therefore, to improve the identification accuracy of the high speed on/off valve’s critical moving characteristics, an identification strategy for detecting the time derivative of the coil current is proposed. First, a mathematical model of the high speed on/off valve (including electromagnetic sub-model and mechanical-fluid sub-model) is established. And on this basis, relationship between the coil current’s derivative and the valve’s critical moving characteristics is analyzed which reveals the changing rule of the coil current’s derivative causing by the ball valve’s moving. Finally, the changing rule of the coil current’s derivative is verified by the comparative simulations and experiments, which also indicate that, with the proposed identification strategy, the maximum identification error of the critical opening/closing time is only within 6%, and the maximum identification error of the total opening/closing time is still small (2.9%), compared to other identification strategies in the previous literatures.

The magnetization and demagnetization process of electrohydraulic servo valve with permanent magnet torque motor is the last manufacturing process of electrohydraulic servo valve before its service, which has a significant effect on the output characteristics and magnetic stability of both torque motor and electrohydraulic servo valve. However, the previous studies mainly focus on the static state of the magnetic circuit instead of the changes of the magnetic steel’s states while operating magnetization and demagnetization process of torque motor, which causes many issues such as the unpredictability and inaccuracy of magnetization and demagnetization process. In this paper, a set of theoretical models are proposed to describe this entire magnetization and demagnetization process more accurately aiming at this issue. Firstly, a detailed magnetic circuit mathematical model of permanent magnet torque motor before demagnetization is established according to two kinds of magnetic circuits. Secondly, different from the existing research, in this paper, taking the variety of internal reluctance and magnetomotive force of magnetic steel into consideration, an equivalent method is presented by dividing the B-H curve of the magnetization and demagnetization process into several segments. Finally, the finite element method is used to verify the accuracy of the proposed mathematical model. The research results show the proposed model can accurately calculate the magnetic flux density of magnetic steel at any time and even the air gap’s magnetic flux and the output torque after the magnetization and demagnetization process. This research can help to design the magnetization and demagnetization process such as demagnetizing current to make sure the toque motor meets the requirements, which has an important guiding significance to design and conduct the magnetization and demagnetization process of electrohydraulic servo valve with permanent magnet torque motor.

Background Recognition of salient MRI morphologic and kinetic features of various malignant tumor subtypes and benign diseases, either visually or with artificial intelligence (AI), allows radiologists to improve diagnoses that may improve patient treatment. Purpose To evaluate whether the diagnostic performance of radiologists in the differentiation of cancer from noncancer at dynamic contrast material-enhanced (DCE) breast MRI is improved when using an AI system compared with conventionally available software. Materials and Methods In a retrospective clinical reader study, images from breast DCE MRI examinations were interpreted by 19 breast imaging radiologists from eight academic and 11 private practices. Readers interpreted each examination twice. In the "first read," they were provided with conventionally available computer-aided evaluation software, including kinetic maps. In the "second read," they were also provided with AI analytics through computer-aided diagnosis software. Reader diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis, with the area under the ROC curve (AUC) as a figure of merit in the task of distinguishing between malignant and benign lesions. The primary study end point was the difference in AUC between the first-read and the second-read conditions. Results One hundred eleven women (mean age, 52 years ± 13 [standard deviation]) were evaluated with a total of 111 breast DCE MRI examinations (54 malignant and 57 nonmalignant lesions). The average AUC of all readers improved from 0.71 to 0.76 (P = .04) when using the AI system. The average sensitivity improved when Breast Imaging Reporting and Data System (BI-RADS) category 3 was used as the cut point (from 90% to 94%; 95% confidence interval [CI] for the change: 0.8%, 7.4%) but not when using BI-RADS category 4a (from 80% to 85%; 95% CI: -0.9%, 11%). The average specificity showed no difference when using either BI-RADS category 4a or category 3 as the cut point (52% and 52% [95% CI: -7.3%, 6.0%], and from 29% to 28% [95% CI: -6.4%, 4.3%], respectively). Conclusion Use of an artificial intelligence system improves radiologists' performance in the task of differentiating benign and malignant MRI breast lesions. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Krupinski in this issue.

The purpose of this study was to compare diagnostic accuracy and interpretation time of screening automated breast ultrasound (ABUS) for women with dense breast tissue without and with use of a recently U.S. Food and Drug Administration-approved computer-aided detection (CAD) system for concurrent read.In a retrospective observer performance study, 18 radiologists interpreted a cancer-enriched set (i.e., cancer prevalence higher than in the original screening cohort) of 185 screening ABUS studies (52 with and 133 without breast cancer). These studies were from a large cohort of ABUS-screened patients interpreted as BI-RADS density C or D. Each reader interpreted each case twice in a counterbalanced study, once without the CAD system and once with it, separated by 4 weeks. For each case, each reader identified abnormal findings and reported BI-RADS assessment category and level of suspicion for breast cancer. Interpretation time was recorded. Level of suspicion data were compared to evaluate diagnostic accuracy by means of the Dorfman-Berbaum-Metz method of jackknife with ANOVA ROC analysis. Interpretation times were compared by ANOVA.The ROC AUC was 0.848 with the CAD system, compared with 0.828 without it, for a difference of 0.020 (95% CI, -0.011 to 0.051) and was statistically noninferior to the AUC without the CAD system with respect to a margin of -0.05 (p = 0.000086). The mean interpretation time was 3 minutes 33 seconds per case without the CAD system and 2 minutes 24 seconds with it, for a difference of 1 minute 9 seconds saved (95% CI, 44-93 seconds; p = 0.000014), or a reduction in interpretation time to 67% of the time without the CAD system.Use of the concurrent-read CAD system for interpretation of screening ABUS studies of women with dense breast tissue who do not have symptoms is expected to make interpretation significantly faster and produce noninferior diagnostic accuracy compared with interpretation without the CAD system.

In the process of reconstruction and expansion of intelligent substation, it is difficult to accurately define the influence scope of SCD file upgrade. In the wake of each modification of SCD file, all configuration information contained in SCD needs to be re-verified, which greatly increases the workload of debugging, operation and maintenance of intelligent substation. Via decoupling SCD files, the problems of modification and re-verification of SCD files in the reconstruction and expansion stage can be tackled. In this paper, SCD precision decoupling method for smart substation with single equipment replacement is proposed, which makes SCD decoupling work more detailed, adaptable to various expansion and technical transformation of substation. The decoupling of SCD is refined from logical structure to physical link level, and the decoupling range of SCD is precisely determined, so as to minimize the modification and reverification range of SCD files and reduce the change risk caused by SCD modification.

Protein-protein interactions (PPIs) have attracted much attention recently because of their preponderant role in most biological processes. The prevention of the interaction between E3 ligase VHL and HIF-1[Formula: see text] may improve tolerance to hypoxia and ameliorate the prognosis of many diseases. To obtain novel potent inhibitors of VHL/HIF-1[Formula: see text] interaction, a series of hydroxyproline-based inhibitors were investigated for structural optimization using a combination of QSAR modeling and molecular docking. Here, 2D- and 3D-QSAR models were developed by genetic function approximation (GFA) and comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods, respectively. The top-ranked models with strict validation revealed satisfactory statistical parameters (CoMFA with [Formula: see text], 0.637; [Formula: see text], 0.955; [Formula: see text], 0.944; CoMSIA with [Formula: see text], 0.649; [Formula: see text], 0.954; [Formula: see text], 0.911; GFA with [Formula: see text], 0.721; [Formula: see text], 0.801; [Formula: see text], 0.861). The selected five 2D-QSAR descriptors were in good accordance with the 3D-QSAR results, and contour maps gave the visualization of feature requirements for inhibitory activity. A new diverse molecular database was created by molecular fragment replacement and BREED techniques for subsequent virtual screening. Eventually, 31 novel hydroxyproline derivatives stood out as potential VHL/HIF-1[Formula: see text] inhibitors with favorable predictions by the CoMFA, CoMSIA and GFA models. The reliability of this protocol suggests that it could also be applied to the exploration of lead optimization of other PPI targets.

Rationale and Objectives Receiver operating characteristic (ROC) analysis for the common image search-and-localize task, in which readers search an image for lesion or lesions not knowing a priori any exists, has been studied for over four decades. However, a satisfactory solution seems elusive. Materials and Methods We show that the ROC curve predictive of clinical outcomes where readers are penalized appropriately for not correctly localizing known lesions cannot be obtained because it is a missing data problem. Further, this ROC curve is between the case-based ROC curve where readers are not penalized and the lesion-based ROC curve where penalty applies. Moreover, the lesion-based ROC curve is the LROC curve proposed by Starr et al. We show maximum-likelihood (ML) estimation of the LROC curve, validation of this procedure with Monte Carlo simulations, and its application to reader ROC datasets. Results Monte Carlo simulations validated ML estimation of area under the LROC curve (AUC) and its variance. Example applications showed that ML estimate of LROC curve fits experimental datasets. Conclusion The ROC curve predictive of clinical performance cannot be estimated from reader ROC data alone because it is a missing data problem, and is between the case-based ROC curve where readers are not penalized for not correctly identifying known lesions and the lesion-based ROC curve where penalty applies. The lesion-based ROC curve is the LROC curve proposed by Starr et al. and can be estimated via ML estimation.

BACKGROUND Osteosarcoma (OS) is a highly aggressive, metastatic bone tumor with a poor prognosis, and occurs more commonly in children and adolescents. Therefore, new drugs and treatments are urgently needed. In this study, we investigated the effect and potential mechanisms of C₁₈H₁₇NO₆ on osteosarcoma cells. MATERIAL AND METHODS Human MNNG osteosarcoma cells were treated with different concentrations of C₁₈H₁₇NO₆. The proliferation of the MNNG cells was examined via CCK-8 assay. Cell migration and invasion were tested via wound-healing assay and Transwell migration and invasion assays. ELISA was used to detect MMP-2, MMP-9, and VEGF secretion. Finally, Western blotting and qRT-PCR were used to detect protein and mRNA expressions, respectively. RESULTS C₁₈H₁₇NO₆ inhibited MNNG proliferation in a dose- and time-dependent manner and inhibited MMP-2, MMP-9, and VEGF secretion. C₁₈H₁₇NO₆ treatment significantly downregulated N-cadherin and Vimentin expression levels and upregulated E-cadherin expression levels in vitro and in vivo. C₁₈H₁₇NO₆ inhibited tumor growth in a MNNG xenograft. We also found that C₁₈H₁₇NO₆ can significantly reduce the phosphorylation of the PI3K/AKT signaling pathway in vivo and in vitro. However, 740Y-P (a PI3K agonist) had the opposite effect on proliferation, migration and invasion of MNNG cells treated with C₁₈H₁₇NO₆. LY294002 (a PI3K inhibitor) downregulated p-PI3K and p-AKT could mimic the inhibitory effect of C₁₈H₁₇NO₆. CONCLUSIONS Our results suggest that C₁₈H₁₇NO₆ can inhibit human MNNG osteosarcoma cell invasion and migration via the PI3K/AKT signaling pathway both in vivo and in vitro. C₁₈H₁₇NO₆ may be a highly effective and low-toxicity natural drug for the prevention or treatment of OS.

In this paper, an improved LBF model based on local regional information is proposed for image segmentation. The basic idea is to add the regularized area term to the energy function of the LBF model and establish a variable coefficient with adaptive capability composed of image regional information. Compared with the LBF model, the proposed model increases the driving force of the evolution curve, making the result better when dealing with the images with weak boundaries and intensity inhomogeneity. At the same time, it effectively solves the problem that the LBF model is sensitive to the initial position and size of the evolution curve. This model is used to segment medical images with complex topological structure and intensity inhomogeneity. Experimental results show that regardless of the initial curve of any position or any size, it has little influence on the segmentation result; moreover, the localization of deep-depressed image boundaries is more accurate, so we get the conclusion that the new model has corresponding improvements in segmentation accuracy and robustness.

OBJECTIVE. The purposes of this study were to evaluate diagnostic parameters measured with ultrafast MRI acquisition and with standard acquisition and to compare diagnostic utility for differentiating benign from malignant lesions. MATERIALS AND METHODS. Ultrafast acquisition is a high-temporal-resolution (7 seconds) imaging technique for obtaining 3D whole-breast images. The dynamic contrast-enhanced 3-T MRI protocol consists of an unenhanced standard and an ultrafast acquisition that includes eight contrast-enhanced ultrafast images and four standard images. Retrospective assessment was performed for 60 patients with 33 malignant and 29 benign lesions. A computer-aided detection system was used to obtain initial enhancement rate and signal enhancement ratio (SER) by means of identification of a voxel showing the highest signal intensity in the first phase of standard imaging. From the same voxel, the enhancement rate at each time point of the ultrafast acquisition and the AUC of the kinetic curve from zero to each time point of ultrafast imaging were obtained. RESULTS. There was a statistically significant difference between benign and malignant lesions in enhancement rate and kinetic AUC for ultrafast imaging and also in initial enhancement rate and SER for standard imaging. ROC analysis showed no significant differences between enhancement rate in ultrafast imaging and SER or initial enhancement rate in standard imaging. CONCLUSION. Ultrafast imaging is useful for discriminating benign from malignant lesions. The differential utility of ultrafast imaging is comparable to that of standard kinetic assessment in a shorter study time.

Objective In lupus nephritis, tubulointerstitial inflammation (TII) is associated with in situ adaptive immune cell networks that amplify local tissue damage. Since conventional therapy appears ineffective for severe TII, and these patients often progress to renal failure, understanding in situ mechanisms might reveal new therapeutic targets. This study was undertaken to assess whether dysregulated apoptotic regulators maintain local adaptive immunity and drive inflammation in TII. Methods This study utilized novel computational approaches that, when applied to multicolor confocal images, quantified apoptotic regulator protein expression in selected lymphocyte subsets. This approach was validated using laser-capture microdissection (LCM) coupled to quantitative polymerase chain reaction (qPCR). Furthermore, the consequences of dysregulated apoptotic mediator expression were explored in a murine model of lupus nephritis. Results Analyses of renal biopsy tissue from patients with lupus nephritis and those with mixed cellular renal allograft rejection revealed that the B cell lymphoma 2 protein (Bcl-2) was frequently expressed in infiltrating lymphocytes, whereas expression of myeloid cell leukemia 1 was low. In contrast, the reciprocal pattern of expression was observed in tonsil germinal centers. These results were consistent with RNA expression data obtained using LCM and qPCR. Bcl-2 was also highly expressed in tubulointerstitial infiltrates in (NZB × NZW)F1 (NZB/NZW) mice. Furthermore, treatment of NZB/NZW mice with ABT-199, a selective oral inhibitor of Bcl-2, prolonged survival and prevented proteinuria and development of TII in a lupus prevention model. Interestingly, glomerular immune complexes were partially ameliorated by ABT-199 treatment, and serum anti-double-stranded DNA antibody titers were unaffected. Conclusion These data demonstrate that Bcl-2 is an attractive therapeutic target in patients with lupus nephritis who manifest TII.

The objective of our study was to evaluate the role of a hybrid T2-weighted imaging-DWI sequence for prostate cancer diagnosis and differentiation of aggressive prostate cancer from nonaggressive prostate cancer.Twenty-one patients with prostate cancer who underwent preoperative 3-T MRI and prostatectomy were included in this study. Patients underwent a hybrid T2-weighted imaging-DWI examination consisting of DW images acquired with TEs of 47, 75, and 100 ms and b values of 0 and 750 s/mm(2). The apparent diffusion coefficient (ADC) and T2 were calculated for cancer and normal prostate ROIs at each TE and b value. Changes in ADC and T2 as a function of increasing the TE and b value, respectively, were analyzed. A new metric termed "PQ4" was defined as the percentage of voxels within an ROI that has increasing T2 with increasing b value and has decreasing ADC with increasing TE.ADC values were significantly higher in normal ROIs than in cancer ROIs at all TEs (p0.0001). With increasing TE, the mean ADC increased 3% in cancer ROIs and increased 12% in normal ROIs. T2 was significantly higher in normal ROIs than in cancer ROIs at both b values (p ≤ 0.0002). The mean T2 decreased with increasing b value in cancer ROIs (ΔT2 = -17 ms) and normal ROIs (ΔT2 = -52 ms). PQ4 clearly differentiated normal ROIs from prostate cancer ROIs (p = 0.0004) and showed significant correlation with Gleason score (ρ = 0.508, p0.0001).Hybrid MRI measures the response of ADC and T2 to changing TEs and b values, respectively. This approach shows promise for detecting prostate cancer and determining its aggressiveness noninvasively.

The objective of our study was to investigate associations between quantitative image features of multiparametric MRI of the prostate and PTEN expression of peripheral zone prostate cancer.A total of 45 peripheral zone cancer foci from 30 patients who had undergone multiparametric prostate MRI before prostatectomy were identified by a genitourinary pathologist and a radiologist who reviewed histologic findings and MR images. Histologic sections of cancer foci underwent immunohistochemical analysis and were scored according to the percentage of tumor-positive cells expressing PTEN as negative (0-20%), mixed (20-80%), or positive (80-100%). Average and 10th percentile apparent diffusion coefficient (ADC) values, skewness of T2-weighted signal intensity histogram, and quantitative perfusion parameters (i.e., forward volume transfer constant [K(trans)], extravascular extracellular volume fraction [ve], and reverse reflux rate constant between the extracellular space and plasma [k(ep)]) from the Tofts model were calculated for each cancer focus. Associations between the quantitative image features and PTEN expression were analyzed with the Spearman rank correlation coefficient (r).Analysis of the 45 cancer foci revealed that 21 (47%) were PTEN-positive, 12 (27%) were PTEN-negative, and 12 (27%) were mixed. There was a weak but significant negative correlation between Gleason score and PTEN expression (r = -0.30, p = 0.04) and between k(ep) and PTEN expression (r = -0.35, p = 0.02). There was no significant correlation between other multiparametric MRI features and PTEN expression.This preliminary study of radiogenomics of peripheral zone prostate cancer revealed weak-but significant-associations between the quantitative dynamic contrast-enhanced MRI feature k(ep) and Gleason score with PTEN expression. These findings warrant further investigation and validation with the aim of using multiparametric MRI to improve risk assessment of patients with prostate cancer.

Rationale and Objectives The aim of the present study was to test the hypothesis that when a radiologist does not perceive an abnormality in images that contain either extremely subtle abnormalities or no abnormalities, the radiologist cannot distinguish these two types of images and the receiver operating characteristic (ROC) curve reflects that performance. Materials and Methods This retrospective study was conducted with approval of our institutional review board. Four general radiologists participated in an observer performance study of 100 chest images, each of which had a 5 × 5 cm region of interest (ROI) drawn (50 containing a lung nodule, and 50 did not, based on computed tomography [CT] confirmation). About half of the lung nodules were extremely subtle. The readers reported their confidence that a nodule was present within the ROI, from which empirical and maximum-likelihood “proper” binormal and conventional binormal ROC curves were estimated. The readers also reported whether they saw an abnormality that could be a nodule within the ROI. Results Empirical ROC curves deviated from typical ROC-curve shapes, and a portion of the curve leading to the northeast corner of the ROC space had relatively steep and constant slopes. The readers reported not seeing anything suggestive of a lung nodule in this portion of the ROC curve, which also corresponded to cases that either contained extremely subtle nodules or normal cases. The average area under the ROC curves (mean ± standard deviation) was 0.66 ± 0.02 for proper binormal, 0.62 ± 0.02 for conventional binormal, and 0.60 ± 0.03 for trapezoidal ROC curves. Conclusions When a radiologist does not perceive an abnormality in images that contain either extremely subtle abnormalities or no abnormalities, the ROC curve (or a portion thereof) is characterized by a straight line, which is not consistent with conventional ROC theories.

Background Risk models have been developed that include the subject’s pretest risk profile and imaging findings to predict the risk of cancer in an objective way. We assessed the accuracy of the Vancouver Lung Cancer Risk Prediction Model compared with that of trainee and experienced radiologists using a subset of size-matched nodules from the National Lung Screening Trial (NLST). Methods One hundred cases from the NLST database were selected (size range, 4-20 mm), including 20 proven cancers and 80 size-matched benign nodules. Three experienced thoracic radiologists and three trainee radiologists were asked to estimate the likelihood of cancer in each case, first independently, and then with knowledge of the model’s risk prediction. The results generated by the model alone also were estimated using receiver operating characteristic (ROC) analysis. The area under the ROC curve (AUC) for each viewing condition was calculated, and statistical significance in their differences was tested by using the Dorfman-Berbaum-Metz method. Results Human observers were more accurate (AUC value of 0.85 ± 0.05 [SD]) than was the model (0.77 ± 0.06) in estimating the risk of malignancy (P = .0010), and use of the model did not improve their accuracy (0.84 ± 0.06). Experienced radiologists performed better than did trainees. Human observers could distinguish benign from malignant nodule morphology more accurately than could the model, which relies mainly on nodule size for risk estimation. Conclusions Experienced and trainee radiologists had superior ability to predict the risk of cancer in size-matched nodules from a screening trial compared with that of the Vancouver model, and use of the model did not improve their accuracy.

SPOCULL is an innovative technology successfully developed by adding a 2nd poly (Poly2, or P2) layer into a mature logic technology as local interconnection (M0), not only the chip area can be reduced significantly but also transistor performance is enhanced. The SPOCULL technology is successfully implemented on 0.13μm CMOS node with logic gate density (∼2x than standard 0.13 μm LL technology) and small SRAM cell (size ∼0.739μm2); this is equivalent to typically 95nm node (thus referred to as 95SPOCULL). Furthermore, the parasitic capacitance and device leakage of transistor is also reduced significantly, e.g. ∼30% leakage reduction with same speed of logic standard cells. Also, the P2 layer enables the one-time-programmable (OTP) and multiple-time-programmable (MTP) capability as embedded into the technology platform for MCU. The SPOCULL can also be easily extended to 0.18 μm node similarly.