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Gleason Grade Group Predictions from mp-MRI of Prostate Cancer Patients using Automated Deep Learning Though histopathology remains the gold standard, there have been significant interests in predicting Gleason Grade using noninvasive imaging such as mp-MRI. Most studies simplify the task into binary classification for the high uncertainty at each group. Handcrafted radiomic features were heavily investigated but prone to errors from the definition of region of interest, feature extraction variations, etc. We proposed an automated deep learning framework (auto-Keras) to predict the group directly based on the 3D data of the whole prostate gland. The training cohort A consisted of 96 PCa patients from SPIE-AAPM-NCI Challenge. The number of patients in each Group was 30, 35, 18, 7, and 6. The testing cohort B consisted of 34 PCa patients from our institute (10, 14, 4, 3, 3). We resampled and rigidly registered ADC and T2WI. N4-bias correction was applied to correct the non-uniformity. For each slice, we performed Gaussian blurring followed by prostate cropping from contour delineated by two clinicians.We tested five scenarios, including input of T2WI, ADC, both, two parallel inputs followed by feature concatenation, and prediction ensemble. The search space of augmentation included translation, flip, rotation, zooming, and contrast. The search space of the architectures had vanilla, ResNet, and Xception. With ADC alone, the model detected 75% of patients in Group 3. Using T2WI and ADC as input, 46% of Group 2 and 40% of Group 1 were identified. Since GG 2 is less aggressive and has a favorable outcome, we further studied the performance of classifying 1 VS. 2-5 and 1-2 VS. 3-5. The models' precision and recall were 91% and 72% for 1-2, 60% and 24% for 3-5. We separated 1 VS. 2-5, with a 96% precision and 73% recall for 2-5. The model had a better performance to predict lower GG when the input contained both T2WI and AD, and better at higher GG when the features were concatenated at the output level. Table 1.Performance of Precision and recall for Gleason Grade Group on the testing cohort.1 VS. 2 VS. 3 VS. 4 VS. 51-2 VS. 3-51 VS. 2-5ADC-onlyGroup 1Group 2Group 3Group 4Group 5Group 1-2Group 3-5Group 1Group 2-5Precision0.100.230.75000.300.500.300.50Recall0.250.380.14--0.580.240.580.24Input MergePrecision0.400.460.25000.910.200.400.61Recall0.310.380.25--0.720.500.310.70Feature MergePrecision0.200.080.250.3300.130.600.200.96Recall0.670.250.250.0600.430.230.670.73PredictionEnsemblePrecision0.200.080.750.3300.170.600.200.91Recall0.500.250.200.10-0.500.240.500.72 Citation Format: Weiwei Zong, Eric Carver, Aharon Feldman, Joon Lee, Zhen Sun, Lanyu Xu, Ali Dabaja, Ning Wen. Gleason grade group predictions from mp-MRI of prostate cancer patients using auto deep learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 186.

The aim of this retrospective analysis is to evaluate the role of stereotactic radiosurgery (SRS) in treating multiple myeloma (MM) of the spine. Medical records of MM patients who underwent single fraction spine SRS between 6/2001 and 12/2014 at our institution were retrospectively reviewed in this institutional review board-approved analysis. Post-treatment radiographic, neurologic, and pain response were the primary endpoints. Endpoints were evaluated with periodic clinical exams and imaging studies (magnetic resonance imaging and computed tomography). Median SRS dose was 16 Gy (10–18) in a single fraction. Seventy-eight patients (121 treatment sites) were treated. Clinical follow-up was available for 71 patients. Radiographic follow-up was available for 94 treatment sites. Median follow-up was 27.8 months (24 days–12.1 years). Radiographic control was observed in 89.4% of the treated sites. Pain relief occurred in 88.3% of the patients that presented with pain; pain progression occurred in 3.3%. Neurological improvement was observed in 63.6% of the patients that presented with a deficit. In sites where MM approached or compressed the epidural canal or the thecal sac, after SRS, evidence of radiographic regression was observed in 87.1%. Toxicities observed included one patient who experienced a tracheoesophageal fistula 2 years after SRS. After SRS, there were 39 VCFs that were potentially SRS-induced. SRS appears to be effective in the treatment of MM of the spine. To the best of our knowledge, this is the largest such experience reported.

Purpose To evaluate the performance of a commercial plastic scintillator detector (PSD) for small-field stereotactic patient-specific quality assurance (QA) measurements using flattening-filter-free beam. Methods A total of ten spherical targets (volume range: [0.03cc-2cc]) were planned with two techniques: (1) Dynamic Conformal Arc (DCA-10 plans), and (2) Volumetric Modulated Arc Therapy (VMAT-10 plans). All plans were generated using Varian Eclipse treatment planning system, and AcurosXB v.13 algorithm in 1.0 mm grid size. Additionally, 14 previously-treated cranial and spine SRS plans were evaluated (6 DCA, 8 VMAT, volume range: [0.04cc-119.02cc]). Plan modulation was quantified via two metrics: MU per prescription dose (MU/Rx) and Average Leaf Pair Opening (ALPO). QA was performed on the Varian Edge linear accelerator equipped with HDMLC. Three detectors were used: (1) PinPoint ion chamber (PTW; active volume 0.015cc), (2) Exradin W1 PSD (Standard Imaging; active volume 0.002cc), and (3) Gafchromic EBT3 film (Ashland). PinPoint chamber and PSD were positioned perpendicular to beam axis in a Lucy phantom (Standard Imaging); films were placed horizontally capturing the coronal plane. Results PSD, film and PinPoint chamber measured average differences of 1.00±1.54%, 1.30±1.69%, and -0.66±2.36% respectively, compared to AcurosXB dose calculation. As the target volume decreased, PinPoint chamber measured lower doses (maximum -5.07% at 0.07cc target), while PSD and film measured higher doses (2.87% and 2.54% at 0.03cc target) than AcurosXB. Film agreed with the benchmark detector PSD by an average difference of 0.31±1.20%, but suffered from larger uncertainty; PinPoint chamber underestimated dose by more than 4% for targets smaller than 0.2cc. Taking PSD as the measurement standard, DCA plans achieved good QA results across all volumes studied, with an average difference of -0.07±0.89%; for VMAT plans, PSD measured consistently higher dose (1.95±1.36%) than AcurosXB. Correlation study revealed that plan modulation quantified by both MU/Rx and ALPO correlated significantly with QA results. Conclusion Among all three detectors, PSD demonstrated superior performances in plans with small fields and heavy modulation. High consistency and low uncertainty made PSD a suitable detector for clinical routine SRS QA. PinPoint chamber should be avoided for targets smaller than 0.2cc; film dosimetry can be utilized with careful evaluation of its uncertainty bracket. Compared to PSD measurements, AcurosXB calculation demonstrated high accuracy for non-modulated small fields. The positive correlation between plan modulation and QA discrepancy calls for our attention for clinical SRS plans with high modulation. This article is protected by copyright. All rights reserved.

Purpose This study aims to extend the observation that the 12Gy-radiosurgical-volume (V12Gy) correlates with the incidence of radiation necrosis in patients with intracranial tumors treated with radiosurgery by using target volume to predict V12Gy. V12Gy based on the target volume was used to predict the radiation necrosis probability (P) directly. Also investigated was the reduction in radiation necrosis rates (ΔP) as a result of optimizing the prescription isodose lines for linac-based SRS. Methods Twenty concentric spherical targets and 22 patients with brain tumors were retrospectively studied. For each case, a standard clinical plan and an optimized plan with prescription isodose lines based on gradient index were created. V12Gy were extracted from both plans to analyze the correlation between V12Gy and target volume. The necrosis probability P as a function of V12Gy was evaluated. To account for variation in prescription, the relation between V12Gy and prescription was also investigated. Results A prediction model for radiation-induced necrosis was presented based on the retrospective study. The model directly relates the typical prescribed dose and the target volume to the radionecrosis probability; V12Gy increased linearly with the target volume (R2>0.99). The linear correlation was then integrated into a logistic model to predict P directly from the target volume. The change in V12Gy as a function of prescription was modeled using a single parameter, s (= -1.15). Relatively large ΔP was observed for target volumes between 7 and 28 cm3 with the maximum reduction (8-9%) occurring at approximately 18 cm3. Conclusions Based on the model results, optimizing the prescription isodose line for target volumes between 7 and 28 cm3 results in a significant reduction in necrosis probability. V12Gy based on the target volume could provide clinicians a predictor of radiation necrosis at the contouring stage thus facilitating treatment decisions. This article is protected by copyright. All rights reserved.

This study details a method to evaluate the source size selection for small field intracranial stereotactic radiosurgery (SRS) deliveries in Eclipse treatment planning system (TPS) for AcurosXB dose calculation algorithm. Our method uses end‐to‐end dosimetric data to evaluate a total of five source size selections (0.50 mm, 0.75 mm, 1.00 mm, 1.25 mm, and 1.50 mm). The dosimetric leaf gap (DLG) was varied in this analysis (three DLG values were tested for each scenario). We also tested two MLC leaf designs (standard and high‐definition MLC) and two delivery types for intracranial SRS (volumetric modulated arc therapy [VMAT] and dynamic conformal arc [DCA]). Thus, a total of 10 VMAT plans and 10 DCA plans were tested for each machine type (TrueBeam [standard MLC] and Edge [high‐definition MLC]). Each plan was mapped to a solid water phantom and dose was calculated with each iteration of source size and DLG value (15 total dose calculations for each plan). To measure the dose, Gafchromic film was placed in the coronal plane of the solid water phantom at isocenter. The phantom was localized via on‐board CBCT and the plans were delivered at planned gantry, collimator, and couch angles. The planned and measured film dose was compared using Gamma (3.0%, 0.3 mm) criteria. The vendor‐recommended 1.00 mm source size was suitable for TrueBeam planning (both VMAT and DCA planning) and Edge DCA planning. However, for Edge VMAT planning, the 0.50 mm source size yielded the highest passing rates. The difference in dose calculation among the source size variations manifested primarily in two regions of the dose calculation: (1) the shoulder of the high‐dose region, and (2) for small targets (volume ≤ 0.30 cc), in the central portion of the high‐dose region. Selection of a larger than optimal source size can result in increased blurring of the shoulder for all target volume sizes tested, and can result in central axis dose discrepancies in excess of 10% for target volumes sizes ≤ 0.30 cc. Our results indicate a need for evaluation of the source size when AcurosXB is used to model intracranial SRS delivery, and our methods represent a feasible process for many clinics to perform tuning of the AcurosXB source size parameter.

As the main inorganic component of human hard tissue, hydroxyapatite (HAp) has attracted extensive interest in biomedical and clinical applications, especially for HAp nanoparticles. In this study, HAp nanorods with a controllable aspect ratio were successfully prepared using NH3·H2O and CO(NH2)2 as aspect ratio modifier by a high-gravity reactive precipitation in a rotating packed bed (RPB) combined with hydrothermal treatment. The influences of the molar ratio of NH3·H2O and CO(NH2)2 and the rotating speed on the average size and aspect ratio of HAp nanorods were systematically explored. The as-synthesized HAp nanorods were investigated with TEM, XRD, and FTIR. The results indicated that the average aspect ratio of HAp nanorods could be facilely controlled in the range 2.2–39. As compared to a traditional batch stirred tank reactor, the RPB reactor had HAp nanorods with a smaller particle width and a wider range of aspect ratio, and a much shorter reaction time from 20 min to 1 s. Further, the potential...

Polymer nanogels/nanocapsules with encapsulation stability, stimuli responsiveness and tumor targeting have emerged as one of the most remarkable carriers for anticancer drug delivery. In this work, we design a multifunctional, four-armed, branched copolymer, PEG–PPS–cRGD, and use it to develop a dual redox-responsive and αvβ3 integrin-targeting nanocapsule via a simple and straightforward self-crosslinking strategy through the disulfide exchange reaction between the polymer arms. The dissolution rate studies illustrate that the PEG–PPS–cRGD nanocapsules had robust drug release profiles under both oxidation and reduction conditions. The in vitro and in vivo investigations demonstrate that the nanocapsules exhibited precise tumor targeting, outstanding antitumor effect and excellent biological safety in the treatment of squamous cell carcinoma. Therefore, this work provides a promising drug delivery platform for cancer therapy and other applications.

Purpose: The aim of this study was to identify and rank discriminant radiomics features extracted from MR multi-modal images to construct an adaptive model for characterization of Dominant Intra-prostatic Lesions (DILs) from normal prostatic gland tissues (NT).Methods and Materials: Two cohorts were retrospectively studied: Group A consisted of 98 patients and Group B 19 patients. Two image modalities were acquired using a 3.0T MR scanner: Axial T2 Weighted (T2W) and axial diffusion weighted (DW) imaging. A linear regression method was used to construct apparent diffusion coefficient (ADC) maps from DW images. DILs and the NT in the mirrored location were drawn on each modality. One hundred and sixty-eight radiomics features were extracted from DILs and NT. A Partial-Least-Squares-Correlation (PLSC) with one-way ANOVA along with bootstrapping ratio techniques were recruited to identify and rank the most discriminant latent variables. An artificial neural network (ANN) was constructed based on the optimal latent variable feature to classify the DILs and NTs. Nineteen patients were randomly chosen to test the contour variability effect on the radiomics analysis and the performance of the ANN. Finally, the trained ANN and a two dimension (2D) convolutional sampling method were combined and used to estimate DIL-NT probability map for two test cases.Results: Among 168 radiomics-based latent variables, only the first four variables of each modality in the PLSC space were found to be significantly different between the DILs and NTs. Area Under Receiver Operating Characteristic (AUROC), Positive Predictive and Negative Predictive values (PPV and NPV) for the conventional method were 94%, 0.95, and 0.92, respectively. When the feature vector was randomly permuted 10,000 times, a very strong permutation-invariant efficiency (p < 0.0001) was achieved. The radiomic-based latent variables of the NTs and DILs showed no statistically significant differences (Fstatistic < Fc = 4.11 with Confidence Level of 95% for all 8 variables) against contour variability. Dice coefficients between DIL-NT probability map and physician contours for the two test cases were 0.82 and 0.71, respectively.Conclusion: This study demonstrates the high performance of combining radiomics information extracted from multimodal MR information such as T2WI and ADC maps, and adaptive models to detect DILs in patients with PCa.

INTRODUCTION Pre-operative differentiation of IDH mutant gliomas from similar appearing pathologies on imaging prior to definitive surgical diagnosis may aid treatment navigation, maximize the surgical approach, and provide diagnostic support for inoperable tumors. Quantitative image feature analysis offers a potential non-invasive method to identify diagnostic, prognostic, and predictive imaging biomarkers. We investigated the use of radiomic MR imaging features to classify tumors based on IDH mutation status. METHOD Pre-operative T1-weighted (T1W), T2-weighted (T2W), T1-contrast enhanced (T1CE), and fluid attenuated inversion recovery (FLAIR) MR brain images, along with patient IDH mutation status (mutant/wildtype) were obtained for 128 glioma patients from The Cancer Genome Atlas (TCGA). Enhancing tumor was delineated by GLISTRboost. GlistrBoost is a hybrid-discriminative model that segments tumors based on an expectation-maximization framework with a classification scheme and uses a probabilistic Bayesian strategy for segmentation refinement. MR studies for 78 glioma patients from six institutions were used for training and 50 glioma patients from a different institution were used for validation. Pre-processing included registration, resampling, and normalization. Cancer Imaging Phenomics Toolkit (CaPTK) extracted 938 radiomic image features per sequence for the enhancing tumor contour. Relevance of each individual feature was determined by the least absolute shrinkage and selection operator (LASSO). The ability of relevant radiomic image features to identify mutation status of IDH was assessed by logistic regression. RESULTS LASSO identified one highly informative radiomic imaging feature, the minimum of the mean absolute histogram deviation on T1 MR images, which was able to predict IDH mutation status with an accuracy of 0.74, precision of 1.0, and recall of 0.32. CONCLUSION Non-invasive prediction of IDH mutation status from pre-surgical MR images offers potential diagnostic, therapeutic, and prognostic benefits for glioma patients. Quantitative image feature analysis is a feasible method for identifying potential radiomic imaging features.

BACKGROUND As the population of Taiwan continues to age rapidly, middle-aged and elderly people will increasingly begin to care for their older relatives. Therefore, the responsibility and complexity of care required from family caregivers will increase. The mobile health technology (mHealth) model has been successfully applied to numerous care services. OBJECTIVE To develop a mobile health app that supports family caregivers of various ages by meeting their home care needs, thus improving their quality of life, decreasing their severity of depression, and making them more empowered. METHODS This study applied a nonrandomized control-group pretest–posttest design. Purposive sampling was employed to recruit 30 family caregivers—16 middle-aged and 14 old family caregivers—from the home care cases of a regional hospital in Taipei. The developed home care mHealth app was used for management and monitoring of patient health. The outcomes measured were quality of life, level of depression, and sense of empowerment. RESULTS The results indicated that use of the mHealth app improved the technology acceptance, quality of life, depression level, and empowerment of the family caregivers. The old caregivers obtained quality of life scores that were 2.23 points higher, on average, than those obtained by the middle-aged caregivers P = .01, a significant difference. On the quality of life questionnaire, the old caregivers’ obtained scores for the health and family factors that were 2.75 P = .01 and 2.49 P = .01 points higher, respectively, than those obtained by the middle-aged caregivers, indicating significant differences. Regarding empowerment and depression, the scores obtained at different time points indicated that both groups became more empowered and less depressed over time, but no significant differences were discovered between the two groups. CONCLUSIONS According to our results, using the home care mHealth app had a positive influence the app is concluded to be a favorable tool for care education and management. Old caregivers found the software useful for managing patients’ physiological data, and they wished that other assistive methods were available to help them understand the internal functions. The software contributes to quality of life improvement, a decrease in depression severity, and empowerment enhancement and can be used by family caregivers as a reference for home care management in the future.

Wang H, Fu Z, Li W, et al. Int J Nanomedicine.019;14:623–638.Errors were found in several images for Figure 5F, 5G, 6A and6B. The authors have advised that mistakes were made duringthe process of organizing the images. A lot of images werecaptured following immunostaining and due to the similarityof these images, several of the same images were incorrectlyselected. The authors and the editor have confirmed that the correctionof the images has no significant impact on the conclusionsof the study. Read the original article

Cancer is a serious threat to human health. Despite extensive research on cancer treatment, there is a growing demand for new therapies. CD147 is widely involved in tumor development, but it is unclear whether cancer cell malignancy is affected by CD147 expression level. The first compound (AC-73) targeting CD147 could only act on advanced tumors and inhibit metastasis. Therefore, new compounds with better anticancer activity should be explored.Wst-1 assays were used to confirm the effect of novel compounds on proliferation. Apoptosis tests were used to evaluate their proapoptotic capacity. A nude mouse model was used to demonstrate in vivo anticancer activity and safety of the compounds. Western blots were used to suggest a molecule mechanism.There is a positive correlation between CD147 expression and tumor cell proliferation. A new compound, HA-08, was synthesized and proved to be more active than AC-73. HA-08 could inhibit cancer cell viability and promote cancer cell apoptosis both in vitro and in vivo. HA-08 induces cancer apoptosis, mainly by disrupting the CD147-CD44 interaction and then down-regulating the JAK/STAT3/Bcl-2 signaling pathway.Our results have clarified the tumor specificity of CD147 and its drug target characteristics. The biological profile of HA-08 suggests that this compound could be developed as a potential anticancer agent.

Introduction: Multiparametric MR imaging (mpMRI) has shown promising results in the diagnosis and localization of prostate cancer. Furthermore, mpMRI may play an important role in identifying the dominant intraprostatic lesion (DIL) for radiotherapy boost. We sought to investigate the level of correlation between dominant tumor foci contoured on various mpMRI sequences. Methods: mpMRI data from 90 patients with MR-guided biopsy-proven prostate cancer were obtained from the SPIE-AAPM-NCI Prostate MR Classification Challenge. Each case consisted of T2-weighted (T2W), apparent diffusion coefficient (ADC), and Ktrans images computed from dynamic contrast-enhanced sequences. All image sets were rigidly co-registered, and the dominant tumor foci were identified and contoured for each MRI sequence. Hausdorff distance (HD), mean distance to agreement (MDA), and Dice and Jaccard coefficients were calculated between the contours for each pair of MRI sequences (i.e., T2 vs. ADC, T2 vs. Ktrans, and ADC vs. Ktrans). The voxel wise spearman correlation was also obtained between these image pairs. Results: The DILs were located in the anterior fibromuscular stroma, central zone, peripheral zone, and transition zone in 35.2, 5.6, 32.4, and 25.4% of patients, respectively. Gleason grade groups 1-5 represented 29.6, 40.8, 15.5, and 14.1% of the study population, respectively (with group grades 4 and 5 analyzed together). The mean contour volumes for the T2W images, and the ADC and Ktrans maps were 2.14 ± 2.1, 2.22 ± 2.2, and 1.84 ± 1.5 mL, respectively. Ktrans values were indistinguishable between cancerous regions and the rest of prostatic regions for 19 patients. The Dice coefficient and Jaccard index were 0.74 ± 0.13, 0.60 ± 0.15 for T2W-ADC and 0.61 ± 0.16, 0.46 ± 0.16 for T2W-Ktrans. The voxel-based Spearman correlations were 0.20 ± 0.20 for T2W-ADC and 0.13 ± 0.25 for T2W-Ktrans. Conclusions: The DIL contoured on T2W images had a high level of agreement with those contoured on ADC maps, but there was little to no quantitative correlation of these results with tumor location and Gleason grade group. Technical hurdles are yet to be solved for precision radiotherapy to target the DILs based on physiological imaging. A Boolean sum volume (BSV) incorporating all available MR sequences may be reasonable in delineating the DIL boost volume.

The globally synchronised introduction of inactivated poliovirus vaccine (IPV) and replacement of trivalent oral poliovirus vaccine (OPV) with bivalent OPV (bOPV) were successfully implemented in China's routine immunisation programme in May, 2016. In response to the global shortage of Salk-strain IPV, Sabin-strain IPV production was encouraged to develop and use in low-income and middle-income countries. We assessed the immunogenicity of the current routine poliovirus vaccination schedule in China and compared it with alternative schedules that use Sabin-strain IPV (sIPV) and bOPV.This open-label, randomised, controlled trial recruited healthy infants aged 60-75 days from two centres in Zhejiang, China. Eligible infants were full-term, due for their first polio vaccination, weighed more than 2·5 kg at birth, were healthy on physical examination with no obvious medical conditions, and had no contraindications to vaccination. Infants were randomly assigned (1:1:1) using permuted block randomisation (block size of 12) to one of three polio vaccination schedules, with the first, second, and third doses given at ages 2 months, 3 months, and 4 months, respectively: sIPV-bOPV-bOPV (1sIPV+2bOPV group; current regimen), sIPV-sIPV-bOPV (2sIPV+1bOPV group), or sIPV-sIPV-sIPV (3sIPV group). The primary endpoint was the proportion of infants with seroconversion to each of the three poliovirus serotypes 1 month after the third dose. Serious and medically important adverse events were monitored for up to 30 days after each vaccination. We assessed immunity in the per-protocol population (all children who completed all three vaccinations and had pre-vaccination and post-vaccination laboratory data) and safety in all children who received at least one dose of study vaccine. This trial is registered with Clinicaltrials.gov, NCT03147560.Between May 1, 2016, and Dec 1, 2017, we enrolled and randomly assigned 528 eligible infants to one of the three treatment groups (176 in each group); 473 infants (158 in the 1sIPV+2bOPV group, 152 in the 2sIPV+1bOPV group, and 163 in the 3sIPV group) were included in the per-protocol population. 100% seroconversion against poliovirus types 1 and 3 was observed in all three groups. Infants who received an immunisation schedule containing bOPV had significantly higher antibody titres against poliovirus types 1 and 3 than did the sIPV-only group (2048 in all three treatment groups; p0·0001). Seroconversion against type 2 poliovirus was observed in 98 (62%) infants in the 1sIPV+2bOPV group, 145 (95%) infants in the 2sIPV+1bOPV group, and 161 (99%) infants in the 3sIPV group. No serious adverse events occurred during the study; 14 minor, transient adverse events were observed, with no significant differences across study groups.All three study schedules were well tolerated and highly immunogenic against poliovirus types 1 and 3. Schedules containing two or three sIPV doses had higher seroconversion rates against poliovirus type 2 than did the schedule with a single dose of sIPV. Our findings support inclusion of two sIPV doses in the routine poliovirus vaccination schedule in China to provide better protection against poliovirus type 2 than provided by the current regimen.Chinese Center for Disease Control and Prevention and China National Biotec Group Company.

Triptolide (TPL) is a traditional Chinese medicine that possesses anti-multidrug resistance (MDR) properties against various cancers, including oral cancer. However, the functional roles of TPL in oral cancer cells and its potential ability to overcome MDR have not fully evaluated. Therefore, in this study we used oral cancer cell line SAS to establish Taxol-resistant cell line SAS/Taxol and investigated the effects of TPL on MDR, proliferation, and apoptosis of SAS/Taxol cells. We first demonstrated that TPL overcame MDR in SAS/Taxol cells. In addition, TPL induced prominent proliferation inhibition, cell cycle arrest, and apoptosis of SAS/Taxol cells. Furthermore, the pro-apoptotic effect of TPL on SAS/Taxol cells was dependent on intrinsic and extrinsic apoptotic pathways involved in the activation of caspases. Consistently, TPL successfully hampered oral tumor growth by inducing cell apoptosis in a xenograft mouse model. Overall, these results indicated that TPL circumvented MDR of SAS/Taxol cells by inhibition of proliferation and induction of apoptosis which was partly mediated by the intrinsic and extrinsic apoptotic pathways, suggesting the potential therapeutic value of TPL on Taxol-resistant human oral cancer.

BACKGROUND Post-discharge care involving telephone follow-up by an enterostomal therapy (ET) nurse is a common form of connected healthcare (cHealth) for post-operative patients with enterostomy. Although telephone follow-up may compensate for the inconvenience of a home visit or a return visit, the present telehomecare cannot completely meet the various needs of patients with enterostomy. Mobile health (mHealth) with apps had shown some promising results in disease management, the success factors for its practical promotion to patients with enterostomy are not elear. The explorations of user experiences are necessary for enhancing the design of cHealth systems. OBJECTIVE The study was aimed to explore the patients’, primary caregivers’, families’, and ET nurses’ health behavior intentions, user experiences, and other recommendations after using the system in telehomecare. METHODS A cHealth system was designed for patients with enterostomy. Two ET nurses, 10 patients (or primary caregivers), and 10 families were recruited for the study. After training, participants were asked to use their mobile applications daily. After 3 patient follow-ups (at the time of enrollment and 1 week and 2 weeks after enrolling), a semi-structured interview was conducted for each participant. Researchers transcribed the interview contents to texts, performed coding with NVivo 11 Pro for Windows (QSR International, Melbourne, Australia) qualitative data analysis Software, and the content through content analysis. RESULTS From the set of stakeholders, 5 patients,5 primary caregivers,10 families and 2 ET nurses were selected. They were all between 21 and 67 years. The results indicated that the stakeholders have 2 primary health behavior intentions: sudden threats and distress and social support and ambient intimacy. There were 3 primary user experiences: intuitive at a glance, self-empowerment and participation and the conflict between utility and value. They also provided some other recommendations for enhancing the design of cHealth systems. CONCLUSIONS This study investigated the health behavior intentions and user experiences of the stakeholders of patients with enterostomy who used mobile apps and a cHealth system for telehomecare and proposed system improvement recommendations. Understanding user experiences and expectations is crucial for system developers to identify the defects in the design of mobile apps and cHealth systems for facilitating the app of cHealth for patients with enterostomy. It is recommended that researchers refer to the recommendations of the users in this study to improve cHealth system designs and to explore the costs and benefits of systems that implement cHealth models for patients after enterostomy.

Background: The globally-synchronized introduction of inactivated poliovirus vaccine (IPV) and replacement of trivalent oral poliovirus vaccine (tOPV) with bivalent oral poliovirus vaccine (bOPV) was successfully implemented in China's routine immunization system in April and May of 2016. We assessed the immunogenicity of the current routine poliovirus vaccination schedule and compared it to alternative schedules that use Sabin-strain IPV (sIPV) and bOPV. Methods: We conducted an open-label, randomized, controlled trial among healthy infants in Zhejiang province, China. After obtaining informed consent, infants were randomly allocated to receive three polio vaccinations at age 2, 3 and 4 months in one of three sequential schedules: sIPV-bOPV-bOPV (Group 1), sIPV-sIPV-bOPV (Group 2), or sIPV-sIPV-sIPV (Group 3). We assessed immunogenicity in the three groups by measuring poliovirus type-specific antibody levels in sera immediately before the first dose and one month after the third dose. We assessed immunity in a per-protocol (PP) analysis (among subjects with no protocol deviations), and assessed safety in an intention-to-treat analysis (among subjects receiving at least one dose of study vaccine). Results: We enrolled and assigned 528 eligible infants to one of the three treatment groups (176 in each group); 473 infants (158 in Group 1, 152 in Group 2, and 163 in Group 3) completed the PP requirements. Three doses of sIPV or bOPV elicited seroconversion in 100% of subjects against poliovirus types 1 and 3 regardless of study group. Infants who received sIPV followed by bOPV had significantly higher antibody titers against poliovirus types 1 and 3 than did the sIPV-only group. Seroconversion against type 2 polio was observed in 62.03% of Group 1 infants, 95.39% of Group 2 infants, and 98.77% of Group 3 infants. The percentages of children with seroprotective antibody titers to poliovirus type 2 after vaccination were 63.29%, 96.05%, and 98.77% in Groups 1, 2, and 3. No serious adverse events occurred during the study; 14 minor, transient adverse events were observed with no significant differences across study groups. Conclusion: All three study schedules were well tolerated and highly immunogenic against poliovirus types 1 and 3. Schedules containing 2 or 3 sIPV doses had higher seroconversion rates against poliovirus type 2 than the schedule with a single dose of sIPV. Our findings support using a two-sIPV-dose routine poliovirus vaccination schedule in China to provide better protection against poliovirus type 2. Clinical Trial Number: The study is registered with ClinicalTrials.gov, number NCT03147560, and has been completed. Funding Statement: The study was funded by Chinese Center for Disease Control and Prevention (funds number: 131031001000150001) and China National Biotec Group Company (CNBG). Declaration of Interests: Yan Liu received grants from Zhejiang provincial basic public welfare research projects (LGF18H260002) and Hangzhou research projects for agricultural and social development (20180533B94). Ethics Approval Statement: The study protocol was approved by the ethics committee of Zhejiang Provincial Center for Disease Control and Prevention. Written informed consent was obtained from legal guardians of the subjects before enrollment.

Disease surveillance is the long-term, continuous, systematic collection of information about diseases and their relevant influencing factors, followed by analysis of the data in a timely manner to guide intervention measures and evaluate their effectiveness. This definition reflects the three basic characteristics of disease surveillance: (1) distributions and trends of diseases can be evaluated only through long-term, continuous, systematic collection of data; (2) original data can be translated to valuable information only through analysis and interpretation of the data; and (3) results can be fully utilized in the real world only after information is provided back to the relevant departments and personnel – hence the importance of timely feedback.

Purpose Deep learning models have had a great success in disease classifications using large data pools of skin cancer images or lung X-rays. However, data scarcity has been the roadblock of applying deep learning models directly on prostate multiparametric MRI (mpMRI). Although model interpretation has been heavily studied for natural images for the past few years, there has been a lack of interpretation of deep learning models trained on medical images. In this paper, an efficient convolutional neural network (CNN) was developed and the model interpretation at various convolutional layers was systematically analyzed to improve the understanding of how CNN interprets multimodality medical images and the predictive powers of features at each layer. The problem of small sample size was addressed by feeding the intermediate features into a traditional classification algorithm known as weighted extreme learning machine (wELM), with imbalanced distribution among output categories taken into consideration. Methods The training data collection used a retrospective set of prostate MR studies, from SPIE-AAPM-NCI PROSTATEx Challenges held in 2017. Three hundred twenty biopsy samples of lesions from 201 prostate cancer patients were diagnosed and identified as clinically significant (malignant) or not significant (benign). All studies included T2-weighted (T2W), proton density-weighted (PD-W), dynamic contrast enhanced (DCE) and diffusion-weighted (DW) imaging. After registration and lesion-based normalization, a CNN with four convolutional layers were developed and trained on tenfold cross validation. The features from intermediate layers were then extracted as input to wELM to test the discriminative power of each individual layer. The best performing model from the tenfolds was chosen to be tested on the holdout cohort from two sources. Feature maps after each convolutional layer were then visualized to monitor the trend, as the layer propagated. Scatter plotting was used to visualize the transformation of data distribution. Finally, a class activation map was generated to highlight the region of interest based on the model perspective. Results Experimental trials indicated that the best input for CNN was a modality combination of T2W, apparent diffusion coefficient (ADC) and DWIb50 . The convolutional features from CNN paired with a weighted extreme learning classifier showed substantial performance compared to a CNN end-to-end training model. The feature map visualization reveals similar findings on natural images where lower layers tend to learn lower level features such as edges, intensity changes, etc, while higher layers learn more abstract and task-related concept such as the lesion region. The generated saliency map revealed that the model was able to focus on the region of interest where the lesion resided and filter out background information, including prostate boundary, rectum, etc. CONCLUSIONS: This work designs a customized workflow for the small and imbalanced dataset of prostate mpMRI where features were extracted from a deep learning model and then analyzed by a traditional machine learning classifier. In addition, this work contributes to revealing how deep learning models interpret mpMRI for prostate cancer patient stratification.

Purpose: This study was designed to evaluate the ability of a U-net neural net-work to properly identify three regions of a brain tumor and an ELM for the prediction of patient overall survival after gross tumor resection using preoperative MR images.

Biomaterial bridging provides physical substrates to guide axonal growth across the lesion. To achieve efficient directional guidance, combinatory strategies using permissive matrix, cells and trophic factors are necessary. In the present study, we evaluated permissive effect of poly (acrylonitrile-co-vinyl chloride) guidance channels filled by different densities of laminin-precoated unidirectional polypropylene filaments combined with Schwann cells, and glial cell line-derived neurotrophic factor for axonal regeneration through a T10 hemisected spinal cord gap in adult rats. We found that channels with filaments significantly reduced the lesion cavity, astrocytic gliosis, and inflammatory responses at the graft-host boundaries. The laminin coated low density filament provided the most favorable directional guidance for axonal regeneration which was enhanced by co-grafting of Schwann cells and glial cell line-derived neurotrophic factor. These results demonstrate that the combinatorial strategy of filament-filled guiding scaffold, adhesive molecular laminin, Schwann cells, and glial cell line-derived neurotrophic factor, provides optimal topographical cues in stimulating directional axonal regeneration following spinal cord injury. This study was approved by Indiana University Institutional Animal Care and Use Committees (IACUC #:11011) on October 29, 2015.

The goal of this study was to investigate small field output factors (OFs) for flat-tening filter-free (FFF) beams on a dedicated stereotactic linear accelerator-based system. From this data, the collimator exchange effect was quantified, and detector-specific correction factors were generated. Output factors for 16 jaw-collimated small fields (from 0.5 to 2 cm) were measured using five different detectors including an ion chamber (CC01), a stereotactic field diode (SFD), a diode detector (Edge), Gafchromic film (EBT3), and a plastic scintillator detector (PSD, W1). Chamber, diodes, and PSD measurements were performed in a Wellhofer water tank, while films were irradiated in solid water at 100 cm source-to-surface distance and 10 cm depth. The collimator exchange effect was quantified for rectangular fields. Monte Carlo (MC) simulations of the measured configurations were also performed using the EGSnrc/DOSXYZnrc code. Output factors measured by the PSD and verified against film and MC calculations were chosen as the benchmark measurements. Compared with plastic scintillator detector (PSD), the small volume ion chamber (CC01) underestimated output factors by an average of -1.0% ± 4.9% (max. = -11.7% for 0.5 × 0.5 cm2 square field). The stereotactic diode (SFD) overestimated output factors by 2.5% ± 0.4% (max. = 3.3% for 0.5 × 1 cm2 rectangular field). The other diode detector (Edge) also overestimated the OFs by an average of 4.2% ± 0.9% (max. = 6.0% for 1 × 1 cm2 square field). Gafchromic film (EBT3) measure-ments and MC calculations agreed with the scintillator detector measurements within 0.6% ± 1.8% and 1.2% ± 1.5%, respectively. Across all the X and Y jaw combinations, the average collimator exchange effect was computed: 1.4% ± 1.1% (CC01), 5.8% ± 5.4% (SFD), 5.1% ± 4.8% (Edge diode), 3.5% ± 5.0% (Monte Carlo), 3.8% ± 4.7% (film), and 5.5% ± 5.1% (PSD). Small field detectors should be used with caution with a clear understanding of their behaviors, especially for FFF beams and small, elongated fields. The scintillator detector exhibited good agreement against Gafchromic film measurements and MC simulations over the range of field sizes studied. The collimator exchange effect was found to be impor-tant at these small field sizes. Detector-specific correction factors were computed using the scintillator measurements as the benchmark.

Purpose: To determine the localization uncertainties associated with 2-dimensional/3-dimensional image registration in comparison to 3-dimensional/3-dimensional image registration in 6 dimensions on a Varian Edge Linac under various imaging conditions. Methods: The systematic errors in 6 dimensions were assessed by comparing automatic 2-dimensional/3-dimensional (kV/MV vs computed tomography) with 3-dimensional/3-dimensional (cone beam computed tomography vs computed tomography) image registrations under various conditions encountered in clinical applications. The 2-dimensional/3-dimensional image registration uncertainties for 88 patients with different treatment sites including intracranial and extracranial were evaluated by statistically analyzing 2-dimensional/3-dimensional pretreatment verification shifts of 192 fractions in stereotactic radiosurgery and stereotactic body radiotherapy. Results: The systematic errors of 2-dimensional/3-dimensional image registration using kV–kV, MV–kV, and MV–MV image pairs were within 0.3 mm and 0.3° for the translational and rotational directions within a 95% confidence interval. No significant difference ( P > .05) in target localization was observed with various computed tomography slice thicknesses (0.8, 1, 2, and 3 mm). Two-dimensional/3-dimensional registration had the best accuracy when pattern intensity and content filter were used. For intracranial sites, means ± standard deviations of translational errors were −0.20 ± 0.70 mm, 0.04 ± 0.50 mm, and 0.10 ± 0.40 mm for the longitudinal, lateral, and vertical directions, respectively. For extracranial sites, means ± standard deviations of translational errors were −0.04 ± 1.00 mm, 0.2 ± 1.0 mm, and 0.1 ± 1.0 mm for the longitudinal, lateral, and vertical directions, respectively. Two-dimensional/3-dimensional image registration for intracranial and extracranial sites had comparable systematic errors that were approximately 0.2 mm in the translational direction and 0.08° in the rotational direction. Conclusion: The standard 2-dimensional/3-dimensional image registration tool available on the Varian Edge radiosurgery device, a state-of-the-art system, is helpful for robust and accurate target positioning for image-guided stereotactic radiosurgery.

// Yu Wang 1, 2, * , Weiwei Zhang 3, * , Li Wen 2, * , Huiling Yang 2, * , Mingling Wen 4 , Yuyu Yun 5 , Lisheng Zhao 2 , Xiaofei Zhu 6 , Li Tian 7 , Erping Luo 3 , Yu Li 5 , Wenchao Liu 1 , Ning Wen 2 1 Department of Oncology, State Key Discipline of Cell Biology, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, China 2 Institute of Stomatology, Chinese PLA General Hospital, Beijing, China 3 Department of Biomedical Engineering, The Fourth Military Medical University, Xi'an, Shaanxi, China 4 Department of Pharmacy, Affiliated Hospital of Academy of Military Medical Sciences, Beijing, China 5 State Key Laboratory of Cancer Biology, Cell Engineering Research Center and Department of Cell Biology, The Fourth Military Medical University, Xi'an, Shaanxi, China 6 Department of Neurology, Kunming General Hospital, Chinese People's Liberation Army, Kunming, Yunnan, China 7 Department of Anesthesiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, China * These authors contributed equally to this work Correspondence to: Yu Li, email: liyufmmu@yahoo.com Wenchao Liu, email: xjcancer@fmmu.edu.cn Ning Wen, email: wenningchn@163.com Keywords: FOXM1, MET, AKT, lung adenocarcinoma, gefitinib Received: January 20, 2016 Accepted: July 18, 2016 Published: August 03, 2016 ABSTRACT Gefitinib resistance remains a major problem in the treatment of lung adenocarcinoma. However, the molecular mechanisms of gefitinib resistance are not fully understood. In this study, we characterized the critical role of transcription factor Forkhead box protein M1 (FOXM1) in gefitinib resistance of lung adenocarcinoma cells. In vitro drug sensitivity assays demonstrated that FOXM1 inhibition sensitized PC9/GR and HCC827/GR cells to gefitinib, whereas FOXM1 overexpression enhanced PC9 and HCC827 cell resistance to gefitinib. Increased FOXM1 resulted in the upregulation of hepatocyte growth factor receptor (MET), which led to activation of the protein kinase B (AKT) pathway, whereas knockdown of FOXM1 did the opposite. FOXM1 bound directly to the MET promoter regions and regulated the promoter activities and the expression of MET at the transcriptional level. Moreover, MET/AKT pathway upregulated the expression of FOXM1 in lung adenocarcinoma cells. Inhibition of pAKT by LY294002 or inhibition of pMET by PHA-665752 significantly inhibited the expression of FOXM1 in lung adenocarcinoma cells. Importantly, we further demonstrated that the expression levels of FOXM1, pAKT and MET were significantly increased in lung adenocarcinoma tissues relative to normal lung tissues, and these three biomarkers were concomitantly overexpressed in lung adenocarcinoma tissues. Taken together, our results indicate that FOXM1 promotes acquired resistance to gefitinib of lung adenocarcinoma cells, and FOXM1 crosstalks with MET/AKT signaling to form a positive feedback loop to promote lung adenocarcinoma development.

Purpose: To evaluate the total systematic accuracy of a frameless, image guided stereotactic radiosurgery system. Methods: The localization accuracy and intermodality difference was determined by delivering radiation to an end-to-end prototype phantom, in which the targets were localized using optical surface monitoring system (OSMS), electromagnetic beacon-based tracking (Calypso®), cone-beam CT, “snap-shot” planar x-ray imaging, and a robotic couch. Six IMRT plans with jaw tracking and a flattening filter free beam were used to study the dosimetric accuracy for intracranial and spinal stereotactic radiosurgerytreatment. Results: End-to-end localization accuracy of the system evaluated with the end-to-end phantom was 0.5 ± 0.2 mm with a maximum deviation of 0.9 mm over 90 measurements (including jaw, MLC, and cone measurements for both auto and manual fusion) for single isocenter, single target treatment, 0.6 ± 0.4 mm for multitarget treatment with shared isocenter. Residual setup errors were within 0.1 mm for OSMS, and 0.3 mm for Calypso. Dosimetric evaluation based on absolute film dosimetry showed greater than 90% pass rate for all cases using a gamma criteria of 3%/1 mm. Conclusions: The authors’ experience demonstrates that the localization accuracy of the frameless image-guided system is comparable to robotic or invasive frame based radiosurgery systems.

This study investigated the effects of estrogen on the bone regeneration potential of periodontal ligament stem cells (PDLSCs) derived from osteoporotic rats and seeded on a collagen-based composite scaffold [nano-hydroxyapatite/collagen/poly(L-lactide) (nHAC/PLA)]. For this purpose, 48 healthy 3‑month-old Sprague-Dawley female rats were divided into 2 groups as follows: the bilaterally ovariectomized (OVX) rats and sham‑operated rats. The PDLSCs were isolated at 3 months after surgery (by which time postmenopausal osteoporosis had developed). The effects of estrogen on the characteristics of these cells seeded in a culture plate and of the cells seeded on nHAC/PLA were then investigated. The PDLSC + nHAC/PLA constructs were implanted subcutaneously into the backs of severe combined immunodeficient (SCID) mice for 12 weeks in order to examine the role of estrogen in the bone formation ability of PDLSCs derived from osteoporotic rats. The results from methyl thiazolyl tetrazolium (MTT) assay revealed that the proliferation of the cells derived from the rats in the OVX group was significantly higher than that of the cells derived from the rats in the sham-operated group at the stage of logarithmic growth. The staining intensity of alkaline phosphatase (ALP) and the mineralization of the cells derived from the rats in the OVX group was significantly weaker than that of the cells from the rats in the sham-operated group. When the PDLSCs were seeded on nHAC/PLA, ALP activity, osteocalcin (OCN) secretion, mineral formation and the mRNA expression levels of ALP, OCN, estrogen receptor (ER)α and ERβ in the cells derived from the rats in the OVX group were markedly decreased. Treatment with 17β-estradiol (E2) significantly weakened the proliferative ability of the cells derived from the OVX group rats, and enhanced their osteogenic differentiation ability and the mRNA expression levels of ALP, OCN, ERα and ERβ. When the constructs were implanted into the backs of SCID mice for 12 weeks, the results of histological analysis indicated that the constructs derived from the OVX group rats had a few newly formed bones and osteoids; however, a great number of newly formed bones and osteoids were present in the ones from the sham-operated group and the OVX + E2 group rats. Our findings further indicate that estrogen deficiency impairs the osteogenic differentiation potential of PDLSCs, and that ER plays an important role in the bone regeneration ability of PDLSCs. Estrogen enhances the bone regeneration potential of PDLSCs derived from osteoporotic rats and seeded on nHAC/PLA. This study may provide insight into the clinical management of periodontal bone tissue repair in postmenopausal women with the use of estrogen-mediated PDLSCs seeded on nHAC/PLA.

Mesenchymal stem cells (MSCs) possess an immunoregulatory capacity and are a therapeutic target for many inflammation‐related diseases. However, the detailed mechanisms of MSC‐mediated immunosuppression remain unclear. In this study, we provide new information to partly explain the molecular mechanisms of immunoregulation by MSCs. Specifically, we found that A20 expression was induced in MSCs by inflammatory cytokines. Knockdown of A20 in MSCs resulted in increased proliferation and reduced adipogenesis, and partly reversed the suppressive effect of MSCs on T cell proliferation in vitro and inhibited tumour growth in vivo. Mechanistic studies indicated that knockdown of A20 in MSCs inhibited activation of the p38 mitogen‐activated protein kinase (MAPK) pathway, which potently promoted the production of tumour necrosis factor (TNF)‐α and inhibited the production of interleukin (IL)‐10. Collectively, these data reveal a crucial role of A20 in regulating the immunomodulatory activities of MSCs by controlling the expression of TNF‐α and IL‐10 in an inflammatory environment. These findings provide novel insights into the pathogenesis of various inflammatory‐associated diseases, and are a new reference for the future development of treatments for such afflictions.

A hot issue in current research regarding stem cells for regenerative medicine is the retainment of the stemness and multipotency of stem cell. Endothelial progenitor cells (EPCs) are characterized by an angiogenic switch that induces angiogenesis and further ameliorates the local microenvironment in ischemic organs. This study investigated whether EPCs could modulate the multipotent and differential abilities of mesenchymal stem cells (MSCs) in vitro and in vivo. We established an EPC/MSC indirect Transwell coculture system and then examined the effects of EPCs on the regulation of MSC biological properties in vitro and bone formation in vivo. The in vitro studies showed that cocultured MSCs (coMSCs) display no overt changes in cell morphology but an enhanced MSC phenotype compared with monocultured MSCs (monoMSCs). Our studies regarding the cellular, molecular, and protein characteristics of coMSCs and monoMSCs demonstrated that EPCs greatly promote the proliferation and differentiation potentials of coMSCs under indirect coculture condition. The expression of the pluripotency factors OCT4, SOX2, Nanog, and Klf4 was also upregulated in coMSCs. Furthermore, coMSCs combined with fibrin glue showed improved bone regeneration when used to repair rat alveolar bone defects compared with monoMSC grafts in vivo. This study is the first to demonstrate that EPCs have dynamic roles in maintaining MSC stemness and regulating MSC differentiation potential.

A calcium phosphate cement (CPC) scaffold has been used to repair bone defects, but its low compressive strength and poor osteogenesis greatly hinder its clinical application. Pectin is a natural, biocompatible, biodegradable, water-soluble polysaccharide that can improve the osteogenic activity of biomaterials. In this study, calcium phosphate/pectin cement (CPCP) scaffolds with different pectin concentrations (2–6%) were prepared. The results showed that changes in the pectin concentration could modulate the morphology of the CPC scaffold. Moreover, CPCP scaffolds can significantly improve the compressive strength of the CPC. For example, the compressive strength reached 28.76 MPa when the concentration of pectin was 6%, which is similar to the mechanical strength of cancellous bone. In addition, the effects of the CPCP scaffolds on cell behaviour were investigated using a model of human adipose-derived stem cells (hADSCs). Our data showed that the introduction of pectin promoted the attachment and proliferation of hADSCs in vitro. Moreover, hADSCs seeded onto the CPCP scaffold showed higher osteogenetic efficacy than those seeded onto the CPC scaffold by modulating the expression of osteogenic genes. Based on these results, a pre-clinical study was performed in New Zealand white rabbits using the cavity defect model. Furthermore, new bone could be observed surrounding the CPCP scaffold within 8 weeks. These results indicate that the CPCP scaffold has potential applications in repairing bone defects.

Neuregulin 4 (Nrg4) is a brown fat-enriched endocrine factor that exerts beneficial metabolic effects on insulin resistance and hepatic steatosis. Autophagy is a mechanism that is essential for preventing hepatic steatosis. The aim of this study was to explore whether Nrg4 ameliorates hepatic steatosis by inducing autophagy. Aged C57BL/6 mice were maintained on a high fat diet with or without Nrg4 intervention for 3 months. Lipid accumulation in the liver was investigated. Autophagy related protein levels along with related signaling pathways that regulate autophagy were evaluated. In addition, the effects of Nrg4 on autophagy were also determined in cultured L-02 cells. Nrg4 decreased high-fat induced intrahepatic lipid content both in vivo and in vitro. Autophagy level in the liver also decreased in obese mice and Nrg4 intervention reactivated autophagy. Further, Nrg4 intervention was found to have activated autophagy via the adenosine monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) signaling pathway. Moreover, when the AMPK/mTOR pathway was suppressed or autophagy was inhibited, the beneficial effects of Nrg4 intervention on hepatic steatosis were diminished. These results indicated that Nrg4 intervention attenuated hepatic steatosis by promoting autophagy in the liver of aged obese mice. Additionally, Nrg4 induced autophagy via the AMPK/mTOR signaling pathway.

Objective: Molecular subtypes have been found to be associated with prognosis and treatment response for prostate cancer (PCa) patients and have the potential to aid personalized treatment planning. We aim to stratify molecular subtypes by lesion characterization from multiparametric magnetic resonance images (mp-MRI) using convolutional neural networks (CNN) and knowledge transferred from lesion malignancy classification task. Methods: We identified 23 PCa patients with available mpMRI and molecular subtype information. Each patient may harbor multi-focal lesions of different molecular subtypes. Automated antibody based dual-color immunohistochemistry assays were developed for the simultaneous assessment of ERG-PTEN and ERG-SPINK1 status in PCa on the whole mount microscopic sections. In 7 patients 11 intraprostatic lesions (ILs) were identified as ERG+, 3 patients 3 ILs as SPINK1+, and 10 patients 11 ILs as triple negative (ERG-, SPINK1- and ETS-). We fed a CNN using intratumoral region of interest defined in a slice-by-slice manner from T2WI, ADC and DWIb50. The feature maps from the third convolutional layer were flattened into 7,744 dimensional vectors to represent each IL slice. To compensate for the small sample size, we utilized transfer learning, from the task of tumor malignancy stratification. The CNN model was pre-trained on mpMRI with 320 ILs from 201 patients for malignancy stratification using a different cohort we published previously, which was later fined tuned on this cohort on malignancy classification for domain adaptation purpose. Results: The clustering accuracy (Top 3 estimates) using cosine similarity metrics was shown in Table 1 for each molecular subtype category respectively. The preliminary results supported our hypothesis that task of lesion malignancy and molecular sub-types stratification were correlated in the imaging features derived from mpMRI. Table 1:Clustering accuracy for each molecular category. Each ILs input had 3 consecutive slices in a sequence, know as 2.5D, to incorporate lesion growth pattern.Accuracy (# of 2.5D image slices)Top 1 predictionsTop 2 predictionsTop 3 predictionsERG+ (21)0.670.900.95SPINK1+ (4)0.50.750.75Negative (17)0.650.760.76 Conclusions: This work showed the potential to classify the molecular subtypes of PCa from mp-MRI. The small sample size problem was tackled using transfer learning. Acknowledgement: The work was supported by a Research Scholar Grant: RSG-15-137-01-CCE from the American Cancer Society. Citation Format: Weiwei Zong, Eric N. Carver, Aharon Feldman, Nallasivam Palanisamy, Ning Wen. Molecular subtype stratification for prostate cancer from mpMRI and histopathology images using convolutional neural networks and transfer learning [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5302.

In order to speed up the power grid engineering 3-D design, strengthen project costs management and control, it is urgent to carry out the research on charging standard for power grid engineering 3-D design, providing guidance for power grid engineering 3-D design. Based on the pilot project of power grid engineering 3-D design, design work day calculation model was constructed, forming a 3-D design charging method covering power grid engineering projects’ every stage. In the future, the 3-D design fee can be adjusted reasonably according to 3-D design work maturity, to improve engineering technology and technical management work.

Purpose Recent advances in deep neural networks (DNNs) have unlocked opportunities for their application for automatic image segmentation. We have evaluated a DNN-based algorithm for automatic segmentation of the prostate gland on a large cohort of patient images. Methods and Materials Planning-CT data sets for 1114 patients with prostate cancer were retrospectively selected and divided into 2 groups. Group A contained 1104 data sets, with 1 physician-generated prostate gland contour for each data set. Among these image sets, 771 were used for training, 193 for validation, and 140 for testing. Group B contained 10 data sets, each including prostate contours delineated by 5 independent physicians and a consensus contour generated using the STAPLE method in the CERR software package. All images were resampled to a spatial resolution of 1 × 1 × 1.5 mm. A region (128 × 128 × 64 voxels) containing the prostate was selected to train a DNN. The best-performing model on the validation data sets was used to segment the prostate on all testing images. Results were compared between DNN and physician-generated contours using the Dice similarity coefficient, Hausdorff distances, regional contour distances, and center-of-mass distances. Results The mean Dice similarity coefficients between DNN-based prostate segmentation and physician-generated contours for test data in Group A, Group B, and Group B-consensus were 0.85 ± 0.06 (range, 0.65-0.93), 0.85 ± 0.04 (range, 0.80-0.91), and 0.88 ± 0.03 (range, 0.82-0.92), respectively. The Hausdorff distance was 7.0 ± 3.5 mm, 7.3 ± 2.0 mm, and 6.3 ± 2.0 mm for Group A, Group B, and Group B-consensus, respectively. The mean center-of-mass distances for all 3 data set groups were within 5 mm. Conclusions A DNN-based algorithm was used to automatically segment the prostate for a large cohort of patients with prostate cancer. DNN-based prostate segmentations were compared to the consensus contour for a smaller group of patients; the agreement between DNN segmentations and consensus contour was similar to the agreement reported in a previous study. Clinical use of DNNs is promising, but further investigation is warranted.

Background Inflammation is a common feature of both peripheral arterial disease (PAD) and periodontitis. Some studies have evaluated the association between PAD and periodontitis. However, there is still no specialized meta-analysis that has quantitatively assessed the strength of the association. Thus, we conducted this meta-analysis to critically assess the strength of the association between PAD and periodontitis. Methods PubMed, Embase, and the Cochrane Library were searched for observational studies of the association between periodontitis and PAD in February 2018. Risk ratios (RRs) and their 95% confidence intervals (CIs) from included studies were pooled to evaluate the strength of the association between periodontitis and PAD. Weighted mean differences (WMDs) and their 95% CIs were pooled to compare the difference in periodontal-related parameters between PAD and non-PAD patients. Results Seven studies including a total of 4307 participants were included in the meta-analysis. The pooled analysis showed that there was a significant difference in the risk of periodontitis between PAD patients and non-PAD participants (RR = 1.70, 95% CI = 1.25–2.29, P = 0.01). There was also a significant difference in number of missing teeth between PAD patients and non-PAD participants (WMD = 3.75, 95% CI = 1.31–6.19, P = 0.003). No significant difference was found in clinical attachment loss between PAD patients and non-PAD participants (WMD = − 0.05, 95% CI = − 0.03–0.19, P = 0.686). Conclusion In conclusion, the results of this meta-analysis revealed a significant relationship between periodontitis and PAD. Moreover, our study indicated that PAD patients had more missing teeth than control subjects did. Further high-quality and well-designed studies with specific inclusion and exclusion criteria are required to strengthen the conclusions of this study. Electronic supplementary material The online version of this article (10.1186/s12872-018-0879-0) contains supplementary material, which is available to authorized users.