Experimental Limits on Solar Reflected Dark Matter with a New Approach on Accelerated-Dark-Matter-Electron Analysis in Semiconductors

Recently a dark matter-electron (DM-electron) paradigm has drawn much attention. Models beyond the standard halo model describing DM accelerated by high energy celestial bodies are under intense examination as well. In this Letter, a velocity components analysis (VCA) method dedicated to swift analysis of accelerated DM-electron interactions via semiconductor detectors is proposed and the first HPGe detector-based accelerated DM-electron analysis is realized. Utilizing the method, the first germanium based constraint on sub-GeV solar reflected DM-electron interaction is presented with the 205.4  kg·day dataset from the CDEX-10 experiment. In the heavy mediator scenario, our result excels in the mass range of 5-15  keV/c^{2}, achieving a 3 orders of magnitude improvement comparing with previous semiconductor experiments. In the light mediator scenario, the strongest laboratory constraint for DM lighter than 0.1  MeV/c^{2} is presented. The result proves the feasibility and demonstrates the vast potential of the VCA technique in future accelerated DM-electron analyses with semiconductor detectors.

[High-risk sexual behaviors of HIV/AIDS and related factors in young students in Guangzhou]

Objective: To explore high-risk sexual behaviors of HIV/AIDS and related factors in young students in Guangzhou. Methods: A cross-sectional survey was conducted in 5 different types of Guangzhou colleges by convenience sampling with minimum number of classes per grade and 600 samples per school from September to November 2021. The R 4.2.2 software was used to consolidate databases. Simultaneously, a logistic regression model and a decision tree algorithm model, stratifying by whether sexual behaviors had occurred before, were constructed. In each layer, the prediction performance of the two models was evaluated through area under receiver operating characteristic and the confusion matrix, and then the model with high prediction performance was retained. Results: A total of 7 346 students were surveyed. The proportion of the respondents reporting sexual experience were 9.08% (667/7 346), in whom 26.24% (175/667) had risky sexual activity in the past year. The decision tree algorithm model performs well in predicting whether high-risk sexual behaviors have occurred in the past year. When the complexity parameter value is 0.018, and nsplit reaches 4, which means there are 5 leaf nodes in the model, the cross error of the tree will be the smallest. The first best grouping variable in the decision tree was whether to use condoms throughout the first sexual behavior. If condoms were used at their sexual debut, but homosexual practices have occurred in the past year, the probability of risky sexual behavior will increase. If homosexual practices have not occurred in the past year, but the age of sexual debut was below 18 years old while the period of HIV education was after high school, the probability of risk sexual behavior will also increase. Conclusions: AIDS-related risky behaviors of young students still deserved attention. The experience of sexual debut and whether AIDS-related health education has been received before the sexual debut were significant predictors for the occurrence of high-risk sexual behavior. The decision tree algorithm model has particular applicability for predicting and screening potential risk populations.

[Perception of HIV-related behavior and influencing factors among young students in Guangzhou]

Objective: To investigate the risk perception for risky behavior of HIV/AIDS infection among young students and to analyze the related influencing factors. Methods: A cross-sectional survey was conducted in 5 different types of Guangzhou colleges from September to November 2021, in which convenience sampling and a minimum number of classes per grade and 600 samples per school were used according to the national unity program. Disordered multi-classification logistic regression was used to construct a risk perception model and analyze influencing factors in different risk perception levels. Results: A total of 7 346 young students were surveyed, and most rated themselves at low risk of HIV/AIDS infections (90.58%, 6 654/7 346). A total of 89.10% (6 545/7 346) of subjects' perception of their HIV/AIDS infection risk was consistent with their risk behavior, while 10.90% (801/7 346) was inconsistent. Among those inconsistent subjects, 19.10% (153/801) showed underestimating their risk , while 80.90% (648/801) seen overestimating their risk. Disordered multi-classification logistic regression analysis showed that, after controlling for other factors, compared with the non-sexual group, respondents whose first sex age under 18 had a higher rate of underestimating their risk of infection (OR=129.39, 95%CI: 73.28-228.48), as well as a higher rate of overestimated their risk of infection (OR=1.76, 95%CI: 1.04-2.99). First sexual intercourse at age 18 or older was a risk factor for underestimating risk (OR=70.56, 95%CI: 42.72-116.53), but was not statistically associated with overestimating risk. Being female, other school type, non-heterosexual orientation, and self-rated HIV-related knowledge as fair or no knowledge were risk factors for overestimating risk but were not statistically associated with underestimating risk. Conclusions: Overall, young students in universities of Guangzhou have a good risk perception of HIV/AIDS infection. Individual factors, education factors and sexual experience will influence students' risk perception of HIV/AIDS infection. Raising the awareness rate of HIV/AIDS knowledge and delaying the age of first sexual intercourse will improve the risk perception ability of young students.

Identification and Automated Delineation of Radioresistant Biological Tumor Volume in Nasopharyngeal Carcinoma Based on Magnetic Resonance Imaging Radiomics

PURPOSE/OBJECTIVE(S)

Widespread use of intensity modulated radiotherapy (IMRT) has improved the tumor control rate of nasopharyngeal carcinoma (NPC). However, nearly 20% of the patients with local-advanced NPC would relapse after precise irradiation and 80% of the recurrent lesions occur within the high dose field, suggesting that there are radiation-resistant cancer cell subsets within the tumor. In this context, identification and contouring of radiation resistance region of NPC for dose escalation at primary IMRT could be advantageous. In this work, we proposed a two-step radiomics workflow to predict local relapse and the recurrent region of NPC before primary IMRT.

MATERIALS/METHODS

In this single-center, retrospective study, pre-treatment magnetic resonance (MR) sequences of T1-weighted imaging (T1-w) and contrast-enhanced T1-weighted imaging (CET1-w) were collected from 800 patients of newly diagnosed and non-metastatic NPC between April 2009 and December 2015. The primary gross tumor volume (GTVp) of all patients and the actual recurrent lesion (GTVr) of patients who suffered from local recurrence were manually contoured for further analysis. A two-step complete radiomics workflow was designed to predict tumor recurrence and segment the region. First, least absolute shrinkage and selection operator (LASSO) was utilized for radiomics features selection of GTVp and support vector machine (SVM) was adopted to predict the recurrence. If the model predicts a recurrence, then the workflow utilizes an improved 3D U-Net to segment the recurrent region. Area under receiver operating characteristic curve (ROC-AUC) was used to evaluate the performance of tumor recurrence prediction, and Dice similarity coefficient (DSC) was used to assess the consistence between the actual and predicted GTVr.

RESULTS

Of 800 NPC patients, 95 (11.9%) patients developed in-field local recurrence. For recurrence risk prediction, the SVM ensemble model (T1-w+CET1-w) was selected for further application with higher sensitivity. The average ROC-AUC, specificity, sensitivity of the SVM ensemble model in a 5-fold cross-validation and in the independent test set of 160 patients were 0.922, 0.922, 0.777 and 0.928, 0.915, 0.737, respectively. Moreover, for recurrent region segmentation, the multi-modality (T1-w+CET1-w) model was superior to the single-modality (T1-w or CET1-w) model. In an independent test set of 15 patients, the DSC, sensitivity and 95% Hausdorff Distance between actual and predicted GTVr was 0.549±0.176, 0.696±0.118 and 9.813±4.788 which was superior to 0.444±0.188, 0.497±0.218 and 12.047±5.361 of original 3D U-Net.

CONCLUSION

The proposed two-step radiomics workflow showed a good performance in predicting tumor recurrence of NPC. The predicted location of the recurrence lesion was all accurate, but there was still a certain difference between the volume of the automated delineated and actual GTVr, which needed to be further optimized to be used as biological tumor volume.

Deep Learning for Automated Contouring of Primary Gross Tumor Volumes by MRI for Radiation Therapy of Brain Metastasis

PURPOSE/OBJECTIVE(S)

Radiotherapy is one of the most effective methods for the treatment of brain metastases (BMs). Traditional manual delineation of primary gross tumor volumes (GTV) of multiple BMs (especially small metastases) in radiotherapy practice is extremely labor intensive and highly dependent on oncologists' experience, achieving the precise and efficient automatic delineation of BMs is of great significance for efficient and homogeneous one-stop adaptive radiotherapy.

MATERIALS/METHODS

We retrospectively collected 62 MRI (non-enhanced T1-weighted sequences) sequences of 50 patients with BMs from January 2020 to July 2021. An automatic model (BUC-Net) for automatic delineation BMs was proposed in this work, which was based on deep learning by combining 3D bottler layer module and the cascade architecture to improve the accuracy and efficient of BMs' automatic delineation, especially for small metastases with tiny size and relatively low contrast. The prosed method was compared with the existing 3D U-Net (U-Net) and 3D U-Net Cascade (U-Net Cascade). The performance of our proposed method was evaluated by Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95) and average surface distance (ASD) with human experts.

RESULTS

The automatic segmentation results of BUC-Net evaluated with 310 BMs in 13 test patients was summarized in Table 1. These BMs in each test patient were automatically delineated by two types of contours: as a whole tumor contour (Whole-delineation) and the multiple tumor contours (Multiple-delineation). BUC-Net performed the best mean DSC and HD95, which is significantly outperformed U-Net (Whole-delineation: 0.911 & 0.894 of DSC, Multiple-delineation: 0.794 & 0.754 of DSC, P < 0.05 for both) and U-Net cascade (Whole-delineation: 0.947 & 7.141 of HD95, Multiple-delineation: 0.902 & 1.171 of HD95, P < 0.05 for both); Additionally, BUC-Net achieved the best mean ASD for Whole-delineation and comparable ASD (0.290 & 0.277, P > 0) for Multiple-delineation with U-Net Cascade.

CONCLUSION

Our results showed that the proposed approach is promising for the automatic delineation of BMs in MRI, which can be integrated into a radiotherapy workflow to significantly shorten segmentation time.

Deep Learning and GAN-Synthesis for Auto-Segmentation of Pancreatic Cancer by Non-Enhanced CT for Adaptive Radiotherapy

PURPOSE/OBJECTIVE(S)

In conventional adaptive radiotherapy (ART) for pancreatic cancer, contrast-enhanced CT (CECT) helps to more precisely delineate primary gross tumor volume (GTV) than non-enhanced CT (NECT). However, frequent use of contrast medium can damage kidneys and prolong treatment time. Moreover, traditional manual delineation is labor-intensive and highly dependent on the experience of oncologists. Currently, automatic delineation based on deep learning with Generative Adversarial Networks (GAN)-based CT synthesis is one of the most feasible solutions to these problems.

MATERIALS/METHODS

A dataset of 35 pancreatic cancer patients was retrospectively collected from May 2021 to December 2022. All patients consist of a pair of NECT and CECT. We designed and developed an automatic delineation framework (Proposed) for GTV of pancreatic cancer based on Trans-cycleGAN and a modified 3D U-Net. TranscycleGAN can not only synthesize CECT from NECT, but can also augment the amount of CT images; then all real and synthesized CT images were used to train the modified 3D U-Net for automatic delineation of GTV; finally, our framework was able to automatically delineate GTV by NECT, but not only by CECT. Our framework was evaluated by dice similarity coefficient (DSC), 95% Harsdorff distance (95HD) and average surface distance (ASD) with oncologists' manual delineation ("gold standard").

RESULTS

The evaluation results were summarized in Table 1. The proposed framework achieved the best automatic delineation results by NECT, which was superior to that of CECT: 0.917 & 0.903 of DSC, 2.498mm & 3.029mm of HD95, 0.481mm & 0.534mm of ASD, p < 0.05 for DSC and HD95. Specifically, it is significantly superior to the automatic delineation results using U-Net by CECT 0.917 & 0.818 of DSC, 2.498mm & 13.228mm of HD95, 0.481mm & 3.633mm of ASD, p < 0.05 for DSC.

CONCLUSION

We proposed an automatic delineation framework for contouring GTV in ART of pancreatic cancer based on deep learning and Trans-cycleGAN network. This framework could automatically delineate GTV and achieve better performance with NECT compared to CECT. Our method could not only reduce the use of contrast medium, but also increase the precision and effectiveness of tumor delineation, which could have a positive impact on precision radiotherapy.

All-in-One Online Radiotherapy for Nasopharyngeal Carcinoma: Preliminary Results of Treatment Time, Contouring Accuracy, Treatment Plan Quality and Patient Compliance

PURPOSE/OBJECTIVE(S)

To explore the feasibility of Fan-beam CT (FBCT)-based all in one (AIO) online workflow for nasopharyngeal carcinoma (NPC) in radical radiotherapy setting, and to preliminarily describe the timing of different steps in the process, contouring accuracy of regions of interest (ROIs), target coverage, organs at risk (OARs) dose and patient compliance.

MATERIALS/METHODS

From March 16, 2022 to January 04, 2023, 25 NPC patients (22/25 diagnosed as phase III/IV disease according to 8th edition of the AJCC/UICC staging system) consecutively treated with AIO radiotherapy were prospectively enrolled. All patients received mask fixation and MRI simulation scan in advance. Primary gross tumor volume (GTVp) of nasopharynx was automatically delineated by AI and edited manually on MRI images. AIO online workflow started with an integrated KV-level CT in a CT-integrated linear accelerator. After that GTVp was registrated to CT images and other ROIs was contoured automatically and then modified manually as needed. Subsequently automatic treatment plan was calculated and optimized until the dose of target and OARs was evaluated satisfactory by physicians and physicists. Finally, treatment was delivered using volumetric modulated arc treatment (VMAT), with prescribed dose of 6996 cGy/ 33 fractions to the GTVp.

RESULTS

Twenty-four patients (24/25, 96%) completed the AIO radiotherapy workflow successfully, with average treatment time of 28.3 min (range: 19.9-42.4 min). the AI-assisted ROIs automatically contouring took 1.55 min in average (range: 1.32-1.77 min), with an average DICE of 97.7% compared with modified contouring, and the average DICE was 95.7% for clinical tumor volume 1 (CTV1), 88.6% for CTV2, 73.6% for GTVn (cervical lymph node), 99.3% for 30 OARs. The automatic treatment plan averagely needed 3.5 min, and the pass rate of radiotherapy planning was 91.7% (22/24). The target coverage for PTVs for GTVp, CTV1, and CTV2 was 99.3%, 99.8%, 98.0% respectively. As for the dose of OARs, the average Dmax of brainstem was 5,583cGy; the Dmax of spinal cord was 3,467cGy; the Dmean of parotid was 3,285 cGy. The average monitor units of all patients was 643 MU and the delivery took 2.93 min. Patient compliance with respect to AIO workflow and total treatment time was excellent.

CONCLUSION

The AIO online radiotherapy was promising for NPC patients, with clinically acceptable AI assisted ROIs contouring and treatment planning, as well as favorable patient compliance to the AIO online workflow.

Automated Contouring of Cervical Lymph Nodes and Clinical Target Volumes for Nasopharyngeal Carcinoma Based on Deep Learning and Experience Constraints

PURPOSE/OBJECTIVE(S)

Application of artificial intelligence (AI) for automated contouring of tumor volumes and organs at risk (OARs) for radiotherapy of nasopharyngeal carcinoma (NPC) leads to improved contouring accuracy and efficiency. However, few studies have involved the automated contouring of gross tumor volume of cervical lymph nodes (GTVn) and clinical target volumes (CTVs). In this work, we proposed an AI automated contouring tool for GTVn and CTVs for radiotherapy of NPC on the plain scans of planning compute tomography (CT).

MATERIALS/METHODS

In this retrospective study, plain scan datasets of planning CT covering the nasopharynx and neck from 139 patients with NPC between March 2022 and December 2022 were collected and divided into training, validation, and testing cohorts of 95, 24, and 20 patients, respectively. Ground truth contours of primary gross tumor volume (GTVp), GTVn (divided into GTVn_L in left neck and GTVn_R in right neck), CTVs (including high risk CTV1 contains GTVp and low risk CTV2 contains GTVp and cervical nodal levels) and OARs were delineated and were defined by consensus of two experts. We first proposed a three-dimensional (3D) U-net using GTVp and OARs as experience constrains to guide the automated delineation of GTVn and CTVs. The average Dice similarity coefficient (DSC) and average surface distance (ASD) were used to quantify the performance of the AI tool. Next, five prospective patients were enrolled for clinical evaluation of our AI tool. DSC between automated contours and radiation oncologist-revised contours and time consuming of the revision were record.

RESULTS

Clinical characteristics of 139 retrospective and 5 prospective patients are list in Table 1. In the independent testing set of 20 patients, our AI tool showed high performance in GTVn and CTVs contouring when compared with the ground truth contours. The mean DSC were 0.73 ± 0.07, 0.74 ± 0.05, 0.93 ± 0.03, and 0.88 ± 0.03, and the mean ASD were 1.01 ± 0.43 mm, 1.14 ± 0.61 mm, 0.51 ± 0.13 mm, 1.17 ± 0.43 mm for GTVn_L, GTVn_R, CTV1 and CTV2, respectively. In the five prospective patients, mean DSC were 0.74 ± 0.07, 0.74 ± 0.10, 0.95 ± 0.01 and 0.89 ± 0.04, respectively. The median time consuming for GTVn and CTVs revision was 2minutes and 10 seconds (range, 1 minutes to 3 minutes).

CONCLUSION

The proposed AI tool integrating clinical experience as constrains showed high accuracy for contouring GTVn and CTVs of NPC. With the assistance of AI contours, contouring efficiency could be probably increased, which is promising in online adaptive radiotherapy of NPC.

First Implementation of Full-Workflow Automation for Online Adaptive Radiotherapy of Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

The aim of this work is to established the technical characteristics and implementation procedures of an artificial intelligence (AI)-powered radiotherapy workflow that enables full-process automation for online adaptive radiotherapy (ART); and evaluate its feasibility and performance implemented for ART of nasopharyngeal carcinoma (NPC).

MATERIALS/METHODS

This single center, prospective study has been approved by the ethical committee of the institution. The online ART workflow was developed based on a CT-integrated linear accelerator. During the course of radiotherapy, the patient underwent daily pre-treatment fan-beam CT (FBCT) scan. Then the FBCT was automatically registered to the original planning CT and used to assess the need for the patient to implement ART according to radiation oncologist's discretionary. The online ART workflow incorporates critical radiotherapy procedures from re-simulation, auto-segmentation by integrating image fusion and deep learning method, auto-replanning, beam delivery, and in vivo quality assurance (QA) into one scheme, while the patient is on the treatment couch during the whole process.

RESULTS

From 2th April 2022 to 5th January 2023, 20 patients with newly-diagnosed, non-metastatic NPC were enrolled in this study. Only one-time online ART was performed for each patient, because that the appropriate timing for triggering online ART was explored in parallel with this study. According to radiation oncologists' discretionary, the median fraction for performing online ART was at 21 fractions (interquartile range, 19-24 fractions). All patients were well tolerated and successfully completed the treatment. For tumor targets contouring, minor revisions were required for automated contours of the primary gross tumor volume (GTVp) and clinical target volumes (CTVs, including CTV1 and CTV2), with the mean DSC between before and after revision of 0.91±0.042, 0.94 ± 0.042 and 0.91 ± 0.061, respectively; and much more revisions for the automated contours of cervical lymph nodes GTV (GTVn), with the mean DSC of 0.74 ± 0.28. The automated contours of normal tissues were clinically acceptable with little modifications. Median time consuming for auto-segmentation and revision was 9.5 minutes (min). For treatment planning, 18 automated plans (90%) were passed at their first auto-optimization and two plans (10%) were passed after further optimization of the dose coverage of CTVs by physicist; and the median time consuming for auto-planning was 6.2 min. Time consuming for other procedures were as follows: re-simulation, 2.3 min; plan evaluation, 3.3 min; beam delivery, 4.6 min; and the duration of the entire process was 25.9 min, range from 19.4 min to 32.5 min.

CONCLUSION

We successfully established an AI-powered online ART workflow for adaptive radiotherapy of NPC, and confirmed that current auto-segmentation and auto-replanning methods are powered enough to support the clinical application of its online ART.

Preserving Structural Consistency in the Generation of Synthetic CT in Pelvic MR-Only Radiation Treatment Planning

PURPOSE/OBJECTIVE(S)

MR-based synthetic CT (sCT) generation is necessary for MR-only radiotherapy to assist in radiation dose calculation, owing to no electronic density information in MR images. This study investigated the feasibility of synthesizing CT images from magnetic resonance (MR) images using generation antagonism networks (GANs) for MR radiotherapy of rectal cancer. Meanwhile, the transformer module and the contrast learning loss were introduced to improve the sCT.

MATERIALS/METHODS

The data set used in this study was the T2-weighted MR and CT image data of 108 patients with rectal cancer. Three-fold cross-validation was performed on all data sets. The transformer module was introduced into the plain CycleGAN, and the improved Patch Noise Contrastive Estimation (PatchNCE) loss was used as the loss function. The improved PatchNCE loss maintained the structural consistency of the MR and the synthetic CT by ensuring the consistency of the distribution of image patches on the MR-sCT image pair. The 2.5D images were taken as the input of our model, which refers to taking two consecutive adjacent layers in a specific layer. The CT-to-sCT image similarity was evaluated by metrics of mean absolute error (MAE), peak signal-to-noise ratio (PSNR), and Structure Similarity Index Measure (SSIM). The sCT dosimetric accuracy was verified against CT-based dose distributions for the photon plan. Relative dose differences in the planning target volume and organs at risk were computed.

RESULTS

The evaluation indicators of sCT images generated by our model were superior to the plain CycleGAN in the results of the three-fold cross-validation. MAE, PSNR and SSIM of our model were 42.850HU, 26.486 and 0.988, respectively, which were superior to 47.129HU, 25.167 and 0.978 of the plain CycleGAN. In addition, sCT generated by our model exhibited good continuity in the axial direction compared with plain CycleGAN. Furthermore, most of the relative differences in the DVH indicators were less than 1%.

CONCLUSION

The accuracy of sCT can be effectively improved by introducing a transformer module and comparative learning loss function. Moreover, all dosimetric differences were within clinically acceptable criteria for photon radiotherapy, demonstrating the feasibility of the MRI-only workflow for patients with rectal cancer.

A Multicenter Study on Deep Learning for Glioblastoma Auto-Segmentation with Prior Knowledge in Multimodal Imaging

PURPOSE/OBJECTIVE(S)

A precise radiotherapy plan is required to ensure accurate delineation of gross tumor volumes (GTV) and clinical target volumes (CTV1 and CTV2) of glioblastomas (GBMs). However, traditional manual delineation is labor intensive and highly dependent on oncologists' experience. To construct and evaluate a deep learning-based automatic delineation method using prior knowledge in multimodal medical imaging to automate precise GTV, CTV1 and CTV2 contouring in GBM patients.

MATERIALS/METHODS

We retrospectively collected the CT and MRI scans of 55 eligible patients with histologically proven high-grade glioma (HGG) from an institute, these scans were performed with non-enhanced CT (CT), contrast-enhanced T1-weighted (T1C) and T2-FLAIR (T2F) sequences. We proposed a two-stage automatic segmentation framework (PKMI-Net) for GTV, CTV1 and CTV2 based on deep learning using prior knowledge in multimodal medical imaging, and its segmentation performance was evaluated with dice similarity coefficient (DSC), 95% Harsdorff distance (HD95), average surface distance (ASD) and relative volume difference (RVD). To further investigate the generalizability of our method, we designed and conducted two evaluation strategies (Mix and Cross) on four multicenter datasets (including 55 patients, 37 patients, 21 patients and 35 patients).

RESULTS

The evaluation results with an 11-patient test set from the single institute were summarized in Table 1, the proposed method demonstrated the best accuracy in segmenting, respectively, GTV, CTV1 and CTV, achieving a DSC of 0.94, 0.95 and 0.92; HD95 of 2.07 mm, 1.18 mm and 3.80 mm; ASD of 0.69 mm, 0.39 mm and 1.13 mm and RVE of 5.50%, 3.97% and 9.68%. In the multicenter evaluation, the segmentation performance of our method implemented with the Cross strategy was comparable to that with the Mix strategy, demonstrating that our method had high and stable generalizability across multicenter datasets in automatically segmenting GTV, CTV1 and CTV2.

CONCLUSION

Our proposed method achieved promising results in automatically segmenting gliomas across various datasets, which could improve the quality and efficiency of glioblastoma radiotherapy.

Prediction of Response to Neoadjuvant Chemoradiotherapy Combined with Pembrolizumab in Esophageal Squamous Cell Carcinoma with CT/FDG PET Radiomic Signatures Based on Machine Learning Classification

PURPOSE/OBJECTIVE(S)

PALACE-1 trial has confirm that the addition of pembrolizumab to neoadjuvant chemoradiotherapy (NCRT) improves the pathological complete response(pCR) for esophageal squamous cell carcinoma (ESCC), which might be a novel treatment strategy for ESCC. In the present study, we aim to establish a machine learning model to predict the local response to NCRT+ pembrolizumab for ESCC by using pretreatment 18-fluorodeoxyglucose positron emission tomography (FDG PET) and contrast-enhanced plan CT images.

MATERIALS/METHODS

A total of 65 cases treated with NCRT+ pembrolizumab followed by surgery were prospectively enrolled for analysis from 2019-2022. Each patient contains a contrast-enhanced plan CT and FDG PET images. 52 patients were randomly divided into training set and 13 patients were used as test set. The Extraction of radiomics features was performed using an open-source Python library PyRadiomics automatically. Features were computed according to the radiologist-drawn ROIs on both CT and PET images. In the feature selection stage least absolute shrinkage and selection operator (LASSO) was utilized on CT features and PET features separately. Four different machine learning models were implemented: Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF) and XGBoost (XGB). The features selected by LASSO regression were used as model input and the output of the model is "pCR" or "non-pCR". To find the optimal parameter, the 5-fold cross-validation method was used in the training stage. In this study, we use accuracy, sensitivity and specificity as the metrics to evaluate the performance of the model on the testing cohort. The predictive performance of the model was assessed using the area under curve (AUC) of the receiver operating characteristics curve (ROC).

RESULTS

Of the 65 cases treated with NCRT+pembrolizumab, 35 patients archived pCR (53.8%), and 30 archived non-pCR. 1684 radiomics features were extracted from each case, and half of them (842 features) were from CT and others were from PET. Among the machine learning models mentioned above SVM achieves the most promising performance on the evaluation metrics. Accuracy, sensitivity, specificity and AUC score on test set were 0.692, 0.833, 0.571 and 0.786 for CT features and 0.615, 0.667, 0.571 and 0.762 for PET features, respectively. For CT+FDG PET fused features accuracy, sensitivity, specificity and AUC score on test set were 0.769, 0.667, 0.857 and 0.833.

CONCLUSION

In this study, we performed several different machine learning models to predict the response to NCRT+ pembrolizumab among ESCC based on the extracted radiomics features from CT and FDG PET images. The best-performing model based on radiomics features of CT and PET images could identify non-pCR to NCRT + pembrolizumab in EC patients.

Dosimetric Benefits of Online Adaptive Radiotherapy in Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

Online adaptive radiotherapy (ART) has the advantage of compensating for potential underdosing to targets and overdosing to organs-at-risk (OARs) caused by variations in patient anatomy and tumor geometry. Artificial intelligence (AI)-assisted rapid generation of new plans makes online ART possible. We aimed to evaluate the dosimetric benefits of online ART on tumor coverage and OARs sparing in nasopharyngeal carcinoma (NPC).

MATERIALS/METHODS

Twenty patients diagnosed with NPC (19 with stage III and 1 with stage II according to the 8th edition of the AJCC/UICC staging system) who underwent definitive radiotherapy or concurrent chemoradiotherapy and received online ART on CT-Linac between April 2022 and December 2022 were included in this study, consisting of 14 males and 6 females with a median age of 48 years (range: 29-68 years). The prescription dose was 6996 cGy/33 fractions for primary gross tumor volume (GTVp), 6600-6996 cGy/33 fractions for gross tumor volume of nodes (GTVn), 6006 cGy/33 fractions for high-risk clinical tumor volume (CTV1), 5412 cGy/33 fractions for low-risk clinical tumor volume (CTV2). The majority of the patients (15/20) received online ART during the fourth to fifth week of their radiotherapy treatment The auto-segmented contours and auto-plan generated by AI were manually reviewed and edited by radiotherapists and physicists. The paired samples t-test was used to compare the dose and volumes metrics of targets and OARs between scheduled plan and online ART plan.

RESULTS

The results of this study showed that compared to the scheduled plan, the online ART plan resulted in significant reductions in the volumes of all targets and 8/12 OARs (temporal lobes, optic nerves, lenses, eyes, parotids, submandibulars, mandibles, and thyroid) (P<0.05). The online ART plan also improved target coverage, with D98% for GTVp in the scheduled plan compared to the online ART plan being 7063.4 ± 76.1 cGy and 7096.1 ± 53.9 cGy (P = 0.1), CTV1 being 6266.7 ± 114.9 cGy and 6208.7 ± 54.7 cGy (P<0.05), and CTV2 being 4142.5 ± 1700.9 cGy and 5416.4 ± 23.8 cGy (P<0.01), respectively. The dose to all 12 OARs was reduced with the use of online ART, with 5/12 OARs showing statistical significance. The D0.03cm3 for the spinal cord in the scheduled plan and online ART plan were 3630.9 ± 197.6 and 3454.1 ± 132.0 cGy; for the temporal lobes were 7075.2 ± 303.0 and 6994.2 ± 345.1 cGy; and 4396.0 ± 2575.0 and for the pituitary were 4214.5 ± 2499.2 cGy. Meanwhile the Dmean for the eyes in the scheduled plan and online ART plan was 769.0 ± 232.0 and 714.8 ± 200.1 cGy; and for the mandibles were 3187.7 ± 211.5 and 3066.0 ± 152.1 cGy.

CONCLUSION

Online ART was effective in protecting most of the OARs in NPC patients, while simultaneously indicating a trend towards enhancing target coverage. This study demonstrated the promising potential of online ART for patients with NPC. This approach will be tested in an upcoming phase III trial.

Small Samples and Low-Cost Auto-Segmentation Method for Pelvic Organ-at-Risk Segmentation in Magnetic Resonance Images Using Deep-Learning

PURPOSE/OBJECTIVE(S)

In radiotherapy, magnetic resonance (MR) imaging has higher contrast of soft tissue, and no radiation compared with computed tomography (CT) scanning. Due to the high-cost of manual annotation, the deep-learning based automatic organ-at-risk (OAR) and target delineation algorithms are in high-demand, but the collecting of large amounts of high-quality annotated datasets remains difficulty. In this paper, we proposed a low-cost OAR segmentation method with semi-supervised annotation using small annotation samples of pelvic MR images.

MATERIALS/METHODS

This study consisted of 94 patients diagnosed with rectal cancer from April 2018 to March 2021 at Peking University People's Hospital. We used 17 slices of MR images with annotation and 78 slices without annotation to train a deep-learning based segmentation model. The bladder, femoral heads, rectum and small intestine were selected as OAR. Semi-supervised method and ensemble learning were used for generating training set using small sample with annotation. Post-processing algorithm was used to correct the self-annotation data. Two of 14 annotation samples were set as test set. As for un-labeled images, 40 of them were set as semi-supervised annotation train set, the rest were test set. Besides, both 2D and 3D auto-segmentation networks were evaluated.

RESULTS

The dice of bladder, femoral head left and right, rectum and small intestine between segmentation results and reference masks is 0.947, 0.983, 0.981, 0.900, 0.845 only using self-annotation and post-processing method of 2D segmentation model. And the dice of corresponding OAR is 0.871, 0.975, 0.975, 0.783, 0.724 using 3D segmentation network, 0.885,0.982, 0.982, 0.882, 0,814 using 2D segmentation network with supervised method (nnUNet). The 2D model outperformed 3D model with better segmentation performance, shorter inference time and fewer parameters.

CONCLUSION

The results proved that we can train a multi-OAR segmentation model only using small annotation samples and other unlabeled samples. Ensemble learning and post-processing methods are necessary for semi-supervised data annotation. For anisotropy data, 2D model shows better performance than 3D models.

Deep Learning-Based Synthesis of Contrast-Enhanced MRI for Automated Delineation of Primary Gross Tumor Volume in Radiotherapy of Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

Contrast-enhanced MRIs are necessary to delineate the primary gross tumor volume (GTVp) in radiotherapy of nasopharyngeal carcinoma (NPC). However, using contrast agents to scan contrast-enhanced MRIs is not applicable to some patients due to metal implants or their allergy, and it increases the treatment cost of patients. To address these problems, this work aims at synthesizing contrast-enhance MRIs from unenhanced MRIs by implementing generative adversarial network (GAN).

MATERIALS/METHODS

In this work, 324 MRI datasets of patients with NPC were retrospectively collected between September 2016 and September 2017 from a single institute. MRI examinations were performed with un-enhanced T1-weighted (T1) and T2-weighted (T2) sequences, and contrast-enhanced T1-weighted (T1C) and fat-suppressed T1-weighted (T1FSC) sequences. We designed and developed a modified pix2pix network to synthesize T1C (sT1C) and T1FSC (sT1FSC) from real T1. The end of the generator in this network was assembled with multiple heads (the classification head and gradient head) to learn more representation information and features from real images, the discriminator in this network distinguished whether the synthesized image is real and fake and supervised that the generator outputs more realistic synthesized image. We verified the performance of the synthesized images for automated delineation of GTVp. In an independent testing set of 11 patients, the synthesized sT1C and sT1FSC were inputted into the segmentation deep learning network along with their corresponding T1 and T2 sequences to generate GTVp contours. Delineation performance of the synthesized images and real images for automated delineation were evaluated by dice similarity coefficient (DSC), and average surface distance (ASD), using human expert contours as the ground truth.

RESULTS

In automated contouring of GTVp for NPC, the segmentation deep learning network using one or two synthesized MRIs showed equivalent performance when compared with the automated contours which generated from four real MRI sequences. Mean DSCs between automated contours by sT1C-replaced or sT1C and sT1FSC-replaced network and ground truth contours were 0.726 ± 0.143 and 0.711 ± 0.157, respectively, slightly inferior to that of contours generated from four real MRI sequences (0.740 ± 0.154, both P >0.05). In terms of mean ASD, there was also no significant difference between automated contours generated from synthesized images and real images (3.056 ± 4.216 mm and 3.537 ± 4.793 mm vs. 3.124 ± 4.637 mm; both P > 0.05).

CONCLUSION

We proposed an MRI-synthesis method based on GAN and the synthesized contrast-enhanced MRIs performed equivalent as the real contrast-enhanced MRIs in the automated delineation of gross tumor volume for radiotherapy of NPC.

Clinical prior Knowledge-Based One-Shot Learning for Automatic Delineation of Clinical Target Volumes in Adaptation Radiotherapy of Cervical Cancer

PURPOSE/OBJECTIVE(S)

Rapid and accurate delineation of clinical target volumes (CTV) of cervical cancer is the crux to ensure the efficiency and benefits of adaptation radiotherapy (ART). However, contour propagation using deformation image registration (DIR) is difficult to ensure the accuracy of CTV contours due to the significant tumor recession in next fraction, and the tumor progress in each fraction is not considered by conventional automatic delineation methods based on deep learning (DL). Currently, one-shot learning (OSL) is feasible to learn the tumor progress from former fractions to improve the accuracy of automatically delineating CTV.

MATERIALS/METHODS

We retrospectively collected 45 patients with cervical cancer from January 2021 to May 2022 in our department. All patients consist of a pair of planning CT and daily CT in ART. A personalized automatic delineation method based on one-shot learning was developed to delineate CTV in daily CT by learning the clinical prior knowledge from the CTV contours and images of planning CT. The performance of our proposed method was evaluated by dice similarity coefficient (DSC), 95% Harsdorff distance (95HD) and average surface distance (ASD) with human experts, and its automatic delineation performance were compared with DIR and DL in daily CT.

RESULTS

Our automatic delineation method OSL performed the best results in all evaluation metrics (denoted by mean ± standard deviation) as shown in Table 1, it is superior to method DL: 0.92 & 0.90 of DSC, 2.33 mm & 2.68 mm of HD95, 0.68 mm & 0.82 mm of ASD, P < 0.05 for DSC and ASD. Specifically, our method is significantly superior to the automatic delineation results by method DIR: 0.92 & 0.84 of DSC, 2.33 mm & 4.11 mm of HD95, 0.68 mm & 1.52 mm of ASD, P < 0.05 for all. In addition, OSL can significantly overcome the delineation problems in fuzzy boundary and delineation missing and perform better generalization for some unusual images, compared with DIR and DL.

CONCLUSION

We proposed an automatic delineation method based on one-shot learning for CTV of cervical cancer in ART, the results demonstrated that the proposed method could improve the precision and generalization of automatically delineating CTV compared against current popular methods. Therefore, it is potential to improve the quality and efficiency of ART for personalized patients and have a positive impact on tumor control and patient survival.

Evidence for Band Renormalizations in Strong-Coupling Superconducting Alkali-Fulleride Films

There has been a long-standing debate about the mechanism of the unusual superconductivity in alkali-intercalated fullerides. In this Letter, using high-resolution angle-resolved photoemission spectroscopy, we systematically investigate the electronic structures of superconducting K_{3}C_{60} thin films. We observe a dispersive energy band crossing the Fermi level with the occupied bandwidth of about 130 meV. The measured band structure shows prominent quasiparticle kinks and a replica band involving the Jahn-Teller active phonon modes, which reflects strong electron-phonon coupling in the system. The electron-phonon coupling constant is estimated to be about 1.2, which dominates the quasiparticle mass renormalization. Moreover, we observe an isotropic nodeless superconducting gap beyond the mean-field estimation (2Δ/k_{B}T_{c}≈5). Both the large electron-phonon coupling constant and large reduced superconducting gap suggest a strong-coupling superconductivity in K_{3}C_{60}, while the electronic correlation effect is suggested by the observation of a waterfall-like band dispersion and the small bandwidth compared with the effective Coulomb interaction. Our results not only directly visualize the crucial band structure but also provide important insights into the mechanism of the unusual superconductivity of fulleride compounds.

Transcutaneous Electrical Acupoints Stimulation Improves Spontaneous Voiding Recovery After Laparoscopic Cholecystectomy: A Randomized Clinical Trial

BACKGROUND

Facilitating the recurrence of spontaneous voiding is considered to be a way to prevent urinary retention after surgery, which is of great importance in cholecystectomy. This study aimed to assess the effect of transcutaneous electrical acupoint stimulation (TEAS) on spontaneous voiding recovery after laparoscopic cholecystectom.

METHODS

Participants who underwent elective laparoscopic cholecystectomy were randomly assigned to either the TEAS group or the sham group. Active TEAS or sham TEAS at specific acupuncture points was conducted intraoperatively and postoperatively. The primary outcome was the recovery speed of spontaneous voiding ability after surgery and secondary outcomes included postoperative urinary retention (POUR), voiding dysfunction, pain, anxiety and depression, and early recovery after surgery.

RESULTS

A total of 1,948 participants were recruited and randomized to TEAS (n = 975) or sham (n = 973) between August 2018 and June 2020. TEAS shortens the time delay of the first spontaneous voiding after laparoscopic cholecystectomy (5.6 h [IQR, 3.7-8.1 h] in the TEAS group vs 7.0 h [IQR, 4.7-9.7 h] in the sham group) (p < 0.001). The TEAS group experienced less POUR (p = 0.020), less voiding difficulty (p < 0.001), less anxiety and depression (p < 0.001), reduced pain (p = 0.007), and earlier ambulation (p = 0.01) than the sham group.

CONCLUSIONS

Our results showed that TEAS is an effective approach to accelerate the recovery of spontaneous voiding and reduce POUR which facilitates recovery for patients after laparoscopic cholecystectomy.

Constraints on Sub-GeV Dark Matter-Electron Scattering from the CDEX-10 Experiment

We present improved germanium-based constraints on sub-GeV dark matter via dark matter-electron (χ-e) scattering using the 205.4  kg·day dataset from the CDEX-10 experiment. Using a novel calculation technique, we attain predicted χ-e scattering spectra observable in high-purity germanium detectors. In the heavy mediator scenario, our results achieve 3 orders of magnitude of improvement for m_{χ} larger than 80  MeV/c^{2} compared to previous germanium-based χ-e results. We also present the most stringent χ-e cross-section limit to date among experiments using solid-state detectors for m_{χ} larger than 90  MeV/c^{2} with heavy mediators and m_{χ} larger than 100  MeV/c^{2} with electric dipole coupling. The result proves the feasibility and demonstrates the vast potential of a new χ-e detection method with high-purity germanium detectors in ultralow radioactive background.

Exotic Dark Matter Search with the CDEX-10 Experiment at China's Jinping Underground Laboratory

A search for exotic dark matter (DM) in the sub-GeV mass range has been conducted using 205 kg day data taken from a p-type point contact germanium detector of the CDEX-10 experiment at China's Jinping underground laboratory. New low-mass dark matter searching channels, neutral current fermionic DM absorption (χ+A→ν+A) and DM-nucleus 3→2 scattering (χ+χ+A→ϕ+A), have been analyzed with an energy threshold of 160 eVee. No significant signal was found; thus new limits on the DM-nucleon interaction cross section are set for both models at the sub-GeV DM mass region. A cross section limit for the fermionic DM absorption is set to be 2.5×10^{-46}  cm^{2} (90% C.L.) at DM mass of 10  MeV/c^{2}. For the DM-nucleus 3→2 scattering scenario, limits are extended to DM mass of 5 and 14  MeV/c^{2} for the massless dark photon and bound DM final state, respectively.

Nicotinamide mononucleotide ameliorates acute lung injury by inducing mitonuclear protein imbalance and activating the UPRmt

Mitochondria need to interact with the nucleus under homeostasis and stress to maintain cellular demands and nuclear transcriptional programs. Disrupted mitonuclear interaction is involved in many disease processes. However, the role of mitonuclear signaling regulators in endotoxin-induced acute lung injury (ALI) remains unknown. Nicotinamide adenine dinucleotide (NAD⁺) is closely related to mitonuclear interaction with its central role in mitochondrial metabolism. In the current study, C57BL/6J mice were administrated with lipopolysaccharide 15 mg/kg to induce endotoxin-induced ALI and investigated whether the NAD⁺ precursor nicotinamide mononucleotide (NMN) could preserve mitonuclear interaction and alleviate ALI. After pretreatment with NMN for 7 days, NAD⁺ levels in the mitochondrial, nucleus, and total intracellular were significantly increased in endotoxemia mice. Moreover, supplementation of NMN alleviated lung pathologic injury, reduced ROS levels, increased MnSOD activities, mitigated mitochondrial dysfunction, ameliorated the defects in the nucleus morphology, and these cytoprotective effects were accompanied by preserving mitonuclear interaction (including mitonuclear protein imbalance and the mitochondrial unfolded protein response, UPR^mt). Furthermore, NAD⁺-mediated mitonuclear protein imbalance and UPR^mt are probably regulated by deacetylase Sirtuin1 (SIRT1). Taken together, our results indicated that NMN pretreatment ameliorated ALI by inducing mitonuclear protein imbalance and activating the UPR^mt in an SIRT1-dependent manner.

[Early efficacy of three dimensional printed anatomical biomimetic cervical artificial disc replacement in the treatment of cervical degenerative diseases]

Objective: To investigate the efficacy and safety of a new cervical artificial disc prosthesis in the treatment of cervical degenerative diseases. Methods: The clinical data of 18 patients with single-level cervical degenerative diseases who underwent three dimensional printed anatomical bionic cervical disc replacement at Department of Spinal Surgery,Honghui Hospital,Xi'an Jiaotong University from May 2019 to July 2020 were analyzed retrospectively. There were 7 males and 11 females,aged (45±8) years old(range:28 to 58 years).The surgical segment was located at C_3－4 level in 2 cases, C_4－5 level in 5 cases, C_5－6 level in 9 cases, and C_6－7 level in 2 cases.The clinical and radiographic outcomes were recorded and compared at preoperative,postoperative times of one month and twelve months.The clinical assessments contained Japanese orthopedic association (JOA) score,neck disability index (NDI) and visual analogue scale (VAS).Imaging assessments included range of motion (ROM) of cervical spine, prosthesis subsidence and prosthesis anteroposterior migration.Repeated measurement variance analysis was used for comparison between groups,and paired t test was used for pairwise comparison. Results: All patients underwent the operation successfully and were followed up for more than 12 months.Compared with preoperative score,the JOA score,NDI and VAS were significantly improved after surgery (all P<0.01).There was no significant difference in postoperative ROM compared with 1-and 12-month preoperative ROM (t=1.570,P=0.135;t=1.744,P=0.099). The prosthesis subsidence was (0.29±0.13) mm (range: 0.18 to 0.50 mm) at 12-month postoperatively.The migration of prosthesis at 12-months postoperatively were (0.71±0.20) mm (range: 0.44 to 1.08 mm).There was no prosthesis subsidence or migration>2 mm at 12-month postoperatively. Conclusion: Three dimensional printed anatomical biomimetic cervical artificial disc replacement has a good early clinical effect in the treatment of cervical degenerative diseases, good mobility can be obtained while maintaining stability.

[G methods for handling time-varying confounding in the longitudinal study]

The conventional analytical methods cannot effectively adjust for time-varying confounding that occur in a longitudinal study and thus cannot correctly estimate the causal effects. This study explains the necessity of precisely controlling time-varying confounding and outlines G methods, including parametric g-formula, inverse probability of weighting, and G-estimation. We also compare the methods above to provide a reference for correctly estimating causal effects in the longitudinal study.

Direct Detection Constraints on Dark Photons with the CDEX-10 Experiment at the China Jinping Underground Laboratory

We report constraints on the dark photon effective kinetic mixing parameter (κ) with data taken from two p-type point-contact germanium detectors of the CDEX-10 experiment at the China Jinping Underground Laboratory. The 90% confidence level upper limits on κ of solar dark photon from 205.4 kg-day exposure are derived, probing new parameter space with masses (m_{V}) from 10 to 300  eV/c^{2} in direct detection experiments. Considering dark photon as the cosmological dark matter, limits at 90% confidence level with m_{V} from 0.1 to 4.0  keV/c^{2} are set from 449.6 kg-day data, with a minimum of κ=1.3×10^{-15} at m_{V}=200  eV/c^{2}.

Constraints on Spin-Independent Nucleus Scattering with sub-GeV Weakly Interacting Massive Particle Dark Matter from the CDEX-1B Experiment at the China Jinping Underground Laboratory

We report results on the searches of weakly interacting massive particles (WIMPs) with sub-GeV masses (m_{χ}) via WIMP-nucleus spin-independent scattering with Migdal effect incorporated. Analysis on time-integrated (TI) and annual modulation (AM) effects on CDEX-1B data are performed, with 737.1 kg day exposure and 160 eVee threshold for TI analysis, and 1107.5 kg day exposure and 250 eVee threshold for AM analysis. The sensitive windows in m_{χ} are expanded by an order of magnitude to lower DM masses with Migdal effect incorporated. New limits on σ_{χN}^{SI} at 90% confidence level are derived as 2×10^{-32}∼7×10^{-35}  cm^{2} for TI analysis at m_{χ}∼50-180  MeV/c^{2}, and 3×10^{-32}∼9×10^{-38}  cm^{2} for AM analysis at m_{χ}∼75  MeV/c^{2}-3.0  GeV/c^{2}.

Incidence and mortality of nasopharyngeal carcinoma: interim analysis of a cluster randomized controlled screening trial (PRO-NPC-001) in southern China

BACKGROUND

Previous mass screening studies have shown that IgA antibodies against Epstein-Barr Virus (EBV) can facilitate early detection of nasopharyngeal carcinoma (NPC), but the impact of EBV-antibody screening for NPC-specific mortality remains unknown.

PATIENTS AND METHODS

A prospective, cluster randomized, controlled trial for NPC screening (PRO-NPC-001) was conducted in 3 selected towns of Zhongshan City and 13 selected towns of Sihui City in southern China beginning in 2008. Serum samples of the screening group were tested for two previously selected anti-EBV antibodies. Subjects with serological medium risk were subsequently retested annually for 3 years, and those with serological high risk were referred to otorhinolaryngologists for diagnostic check-up. An interim analysis was carried out to evaluate the primary end points of the NPC-specific mortality and the early diagnostic rate, and the secondary end point of the NPC incidence, through linkage with the database of Zhongshan City.

RESULTS

Among 70 296 total subjects, 29 413 screened participants (41.8% of the total subjects) in the screening group and 50 636 in the control group, 153 (43.3 per 100 000 person-year), 62 (55.3 per 100 000 person-year) and 99 (33.1 per 100 000 person-year) NPC cases were identified. The early diagnostic rates of NPC were significantly higher in the participants (79.0%, P < 0.0001) and the screening group (45.9%, P < 0.0001) compared with the control group (20.6%). Although no differences were found between NPC-specific mortality of the screening group and the control group [relative risk (RR)= 0.82, 95% confidence interval (CI) 0.37-1.79], lower NPC-specific mortality was noticed among participants from the screening group versus the control group (RR = 0.22, 95% CI 0.09-0.49).

CONCLUSION

IgA antibodies against EBV can identify high-risk population and was effective in screening for early asymptomatic NPC. Although the mortality reduction was not significant in the primary end point, we noted encouraging evidence of a mortality reduction in screening participants in this interim analysis.

CLINICAL TRIAL NUMBER

NCT00941538.

[Prognostic factors of patients with T2N0M0 upper tract urothelial carcinoma: a single-center retrospective study of 235 patients]

OBJECTIVE

To evaluate the impacts of the prognostic factors of T2N0M0 upper tract urothelial carcinoma (UTUC) for Chinese patients.

METHODS

A retrospective study was conducted including 235 patients who were diagnosed with T2N0M0 UTUC in our hospital and received radical nephroureterectomy (RNU) or partial ureterectomy during January 2000 and December 2013. The 3 and 5-year cancer-specific survival rates and bladder recurrence-free survival rates of all the patients were valued using Kaplan-Meier method, and the survival curves with statistical significance between the two were compared using the Log-rank test. Variables with significant differences in the univariate analysis were subjected to the multivariate analysis by Cox regression model.

RESULTS

A total of 235 patients were included in this study, including 95 (40.4%) male patients and 140 (59.6%) female patients. The mean age was 66.73±10.49 years.The median follow-up time was 53 (rang: 3-142) months, and during the follow-up, 74 (31.5%) patients died of UTUC after a median of 35 months,and 96 (40.9%) patients developed intravesical recurrence after a median of 19.5 months. The 3 and 5-year cancer-specific survival rates of all the patients were 89.1% and 85.9%, respectively; the bladder recurrence-free survival rates were 85.5% and 80.2%, respectively. The independent prognostic factors of cancer-specific mortality were tumor age elder than 55 years (HR=3.138, 95%CI: 1.348-7.306, P=0.008) and diameter larger than 5 cm (HR=3.320, 95%CI: 1.882-5.857, P<0.001). The independent prognostic factors of bladder recurrence-free survival were ureter tumor (HR=1.757, 95%CI: 1.159-2.664, P=0.008) and lower tumor grade (HR=1.760, 95% CI: 1.151-2.692, P=0.009).

CONCLUSION

T2N0M0 UTUC has a better cancer-specific survival. The intravesical recurrence was equivalent to non-muscle invasive UTUC but earlier. The tumor diameter larger than 5 cm and the patient age elder than 55 years were independently associated with cancer-specific mortality; the primary tumor located in ureter and lower tumor grade were more likely to develop intravesical recurrence.

[Nuclear export signal of androgen receptor regulated of androgen receptor stability in prostate cancer]

OBJECTIVE

To investigate the mechanisms of nuclear export signal of androgen receptor (NES^AR) in the regulation of androgen receptor (AR) protein expression and stability in prostate cancer.

METHODS

The green fluorescent protein fusion protein expression vectors pEGFP-AR(1-918aa), pEGFP-NES^AR (743-817aa), pEGFP-NAR (1-665aa) and pEGFP-NAR-NES^AR, and lysine mutants of NES^AR pEGFP-NES^AR K776R, pEGFP-NES^AR K807R and pEGFP-NES^AR K776R/K807R, were transiently transfected into prostate cancer cell line PC3. Fluorescence microscopy, Western blot and immunoprecipitation were used to detect NES^AR regulation of androgen receptor stability.

RESULTS

Under the fluorescence microscope, NES^AR-containing fusion proteins were cytoplasmic localization, and their fluorescence intensities were much weaker than those without NES^AR. The expression levels of NES^AR-containing fusion proteins were significantly lower than those without NES^AR. The half-lives of GFP-NES^AR and GFP-NAR-NES^AR were less than 6 h, while the expression of GFP and GFP-NAR was relatively stable and the half-life was more than 24 h in the presence of cycloheximide. The expression levels of GFP-NES^AR were significantly increased by proteasome inhibitor MG132 treatment in a dose-dependent manner; in contrast, MG132 did not show any significant effect on the protein levels of GFP. When new protein synthesis was blocked, MG132 could also prevent the degradation of GFP-NES^AR in the transfected cells in the presence of cycloheximide, while it had no significant effect on GFP protein stability in the parallel experiment. GFP immunoprecipitation showed that the ubiquitination level of GFP-NES^AR fusion protein was significantly higher than that of the GFP control. The mutations of lysine sites K776 and K807 in NES^AR significantly reduced the level of ubiquitination, and showed increased protein stability, indicating that they were the key amino acid residues of NES^AR ubiquitination.

CONCLUSION

NES^AR was unstable and decreased the stability of its fusion proteins. NES^AR was the target of polyubiquitination and mediated the degradation of its fusion proteins through the ubiquitin-proteasome pathway in prostate cancer cells. Our research provides a new way to regulate the level and/or activity of AR proteins, thus helping us understand the molecular mechanisms of AR degradation and strict control of AR in the progression to castration-resistance.

Multiple ancient horizontal gene transfers and duplications in lepidopteran species

Eukaryotic horizontal gene transfer (HGT) events are increasingly being discovered yet few reports have summarized multiple occurrences in a wide range of species. We systematically investigated HGT events in the order Lepidoptera by employing a series of filters. Bombyx mori, Danaus plexippus and Heliconius melpomene had 13, 12 and 12 HGTs, respectively, from bacteria and fungi. These HGTs contributed a total of 64 predicted genes: 22 to B. mori, 22 to D. plexippus and 20 to H. melpomene. Several new genes were generated by post-transfer duplications. Post-transfer duplication of a suite of functional HGTs has rarely been reported in higher organisms. The distributional patterns of paralogues for certain genes differed in the three species, indicating potential independent duplication or loss events. All of these HGTs had homologues expressed in some other lepidopterans, indicating ancient transfer events. Most HGTs were involved in the metabolism of sugar and amino acids. These HGTs appeared to have experienced amelioration, purifying selection and accelerated evolution to adapt to the background genome of the recipient. The discovery of ancient, massive HGTs and duplications in lepidopterans and their adaptive evolution provides further insights into the evolutionary significance of the events from donors to multicellular host recipients.

Junction temperature measurement of light emitting diode by electroluminescence

Junction temperature (JT) is a key parameter of the performance and lifetime of light emitting diodes (LEDs). In this paper, a mobile instrument system has been developed for the non-contact measurement of JTs of LED under LabVIEW control. The electroluminescence (EL) peak shift of the LED is explored to measure the JT. Commercially available high power blue LEDs are measured. A linear relation between emission peak shift and JT is found. The accuracy of the JT is about 1 °C determined by the precision of the emission peak shift, ±0.03 nm, at 3σ standard deviation for blue LED. Using this system, on-line temperature rise curves of LED lamps are determined.

Prevalence of obesity and associated risk factors in Northeastern China

AIM

To investigate the prevalence of obesity and associated risk factors in the Northeastern Chinese city of Dehui.

METHODS

A cross-sectional study involving random sampling methods generated 3598 completed questionnaires by permanent residents of Dehui. Binary multivariate logistic regression analysis was used to identify factors that were significantly associated with obesity.

RESULTS

Based on the 2000 WHO diagnostic criterion regarding populations in the Asia-Pacific region, the prevalence of obesity was 37.71% (34.77% of females; 41.11% of males). Elevated body mass index (BMI) was significantly associated with cardiovascular disease (CVD)-associated conditions (P<0.05), and increased prevalence of abnormally high transaminase levels (P<0.05). Binary logistic regression analysis demonstrated the following variables were associated with obesity: increased age (odds ratio [OR]: 1.01, 95% confidence interval [CI]: 1.0-1.02), high total cholesterol (TC) (OR: 1.26, 95% CI: 1.03-1.54), high triglycerides (TG) (OR: 1.38, 95% CI: 1.16-1.64), hypertension (OR: 1.62, 95% CI: 1.39-1.90), fatty liver (OR: 2.91, 95% CI: 2.41-3.49), living in an urban setting (OR: 2.84, 95% CI: 2.39-3.38), and advanced education (OR: 1.22, 95% CI: 1.06-1.40).

CONCLUSIONS

Obesity is prevalent among the adult population in Northeastern China and is significantly associated with CVD risk factors such as hypertension, dyslipidemia, as well as transaminase abnormalities.

Epidemiological Investigation of Metabolic Syndrome and Analysis of Relevant Factors in North-Eastern China

This epidemiological study was conducted to investigate the prevalence of metabolic syndrome and associated risk factors in Chinese subjects from Dehui in northeastern China. Using a random sampling method, a questionnaire was completed by 3785 permanent residents aged 18-72 years and relevant clinical data were collected from each subject. Binary multivariate logistic regression analysis was used to identify factors that were significantly associated with metabolic syndrome. Based on the International Diabetes Federation definition, the prevalence of metabolic syndrome was 22.4%, which is higher than that of the general Chinese population. Metabolic syndrome occurred more frequently in females and the prevalence gradually increased with age. Living in an urban setting and being female, > 50 years old, overweight, having total cholesterol ≥ 5.18 mmol/l, low-density lipoprotein cholesterol ≥ 3.1 mmol/l, and a fatty liver were significant risk factors associated with metabolic syndrome.

Systemic lupus erythematosus: a genetic epidemiology study of 695 patients from China

Our purpose was to explore potential genetic models for systemic lupus erythematosus (SLE) and analyze genetic epidemiologic characteristics of SLE in a Chinese population. Data for 695 patients with SLE were obtained by using a uniform questionnaire. Patients, clinical characteristics and their family history were analyzed using software. A complex segregation analysis was conducted to propose potential genetic models for SLE. The mean +/- SD age of onset were 30.2 +/- 10.5 years and mean time to progression to SLE was 32.5 +/- 44.4 months. The most frequent initial manifestations were malar rash (61.3%). During the evolution of the disease, the main clinical features were arthritis in 73.6% of our patients, followed by malar rash (68.1%), and renal involvement (56.7%). As the first symptom, the late-onset group (onset of disease beyond the age of 50 years) less often showed malar rash (45% vs. 63.4% in the early-onset group; p = 0.001). There were no significant differences in the other cumulative clinical symptoms between late-onset and early-onset group, except for a lower prevalence of malar rash, photosensitivity and alopecia and a higher prevalence of mucosal ulcers in the late-onset group. A positive family history of SLE was obtained in 50 patients (7.2%). There were no statistical differences in clinical characteristics between familial SLE and sporadic SLE patients. The heritability of SLE was 43.6%, the genetic model of SLE could be polygenetic model and major gene mode is the best fitted one. SLE could be a multifactorial disease with polygenetic model.

[Studies on distribution of magnetic gelatin microspheres in rabbits]

In this report, the technique of labelling MG-ms with 99mTc as pertechnetate in the presence of a reducing agent such as SnCl2 was described. The distribution of intravenously injected 99mTc-labelled MG-ms in rabbits at different intervals of magnetic field applied and different magnetic field intensity was investigated by using an externally applied magnetic field and measuring the radioactivity at the rabbit head and other organs. When magnet was used, the radioactivity in the head, target site, was 15 times more than that when magnet was not used. At the same time, the radioactivity of the lung was 5 times less than when magnet was not used. The newly designed magnetic field equipment was presented.

Hprt mutations and karyotype abnormalities in T-cell clones from healthy subjects and melphalan-treated ovarian carcinoma patients

In vivo mutations at the locus for hypoxanthine phosphoribosyl transferase (hprt) were studied in 6-thioguanine (TG)-resistant T-lymphocyte clones from healthy male and female subjects and ovarian carcinoma patients treated with melphalan. Southern blot analysis of 108 clones showed alterations in 14% (4/29) of the clones from healthy males, 4.3% (2/47) of the clones from healthy females and 3.1% (1/32) of the clones from melphalan-treated patients. 2 of the 7 abnormal clones had a total deletion of the hprt gene; the others had partial deletions. Karyotype analysis of 82 clones revealed 1 clonal abnormality in 29 mutant clones from healthy males (3.6%). Loss or structural aberration of 1 X-chromosome occurred in 6% of the clones from healthy females. The frequency of karyotypic abnormalities (excluding those affecting one of the X-chromosomes) was significantly higher in clones from patients (37%) as compared to healthy females (5.9%). No aberration was found to affect the hprt locus at Xq27 in any of the 82 clones studied.

Induction and persistence of SCE-inducing damage in human lymphocytes exposed to vinyl acetate and acetaldehyde in vitro

The frequency of sister-chromatid exchange (SCE) was studied in cultures of human lymphocytes exposed to vinyl acetate (VA) or acetaldehyde (AA) for various time periods and in different phases of the cell cycle. Equimolar concentrations (0.1-2.4 mM) of VA and AA were found to induce very similar, dose-dependent increases of SCE. The SCE frequency in cells treated with VA was found to increase linearly with exposure times up to 24 h. Cells exposed to VA or AA in the late G1-phase of the cell cycle showed a 2-fold higher SCE frequency than cells exposed in early G1. Cultures treated with VA in the first G1-phase showed a significant increase of SCE during 3 subsequent cell cycles. These results indicate that (1) AA is likely to be responsible for the SCE induction observed in VA-treated cells, (2) the SCE-inducing activity of AA persists for several cell cycles in vitro, and (3) removal of SCE-inducing AA-damage occurs during G1. Taken together, the data suggest that AA has a slow turn-over in human lymphocytes in vitro, and may accumulate in the cells, possibly by forming reversible Schiff bases, and when released gives rise to SCE-inducing DNA cross-links.

DNA cross-links in human leucocytes treated with vinyl acetate and acetaldehyde in vitro

Human leucocytes were incubated in the presence of vinyl acetate or acetaldehyde (10-20 mM) for 4 h at 37 degrees C in vitro. DNA damage was analysed by alkaline elution. None of the compounds induced a detectable increase in the frequency of DNA strand breaks. Cells exposed to 5 Gy of X-ray immediately after treatment and before alkaline elution showed a clear, dose-dependent retardation of the elution rate in comparison with X-irradiated control cells. These results demonstrate that both vinyl acetate and acetaldehyde induce DNA cross-links in human cells.