Purpose: To develop an automated treatment planning strategy for external beam intensity-modulated radiation therapy (IMRT), including a deep learning-based three-dimensional (3D) dose prediction and a dose distribution-based plan generation algorithm. Methods and Materials: A residual neural network-based deep learning model is trained to predict a dose distribution based on patient-specific geometry and prescription dose. A total of 270 headand-neck cancer cases were enrolled in this study, including 195 cases in the training dataset, 25 cases in the validation dataset, and 50 cases in the testing dataset. All patients were treated with IMRT with a variety of different prescription patterns. The model input consists of CT images and contours delineating the organs at risk (OARs) and planning target volumes (PTVs). The algorithm output is trained to predict the dose distribution on the CT image slices. The obtained prediction model is used to predict dose distributions for new patients. Then, an optimization objective function based on these predicted dose distributions is created for automatic plan generation. Results: Our results demonstrate that the deep learning method can predict clinically acceptable dose distributions. There is no statistically significant difference between prediction and real clinical plan for all clinically relevant dose-volume histogram (DVH) indices, except brainstem, right and left lens. However, the predicted plans were still clinically acceptable. The results of plan generation show no statistically significant differences between the automatic generated plan and the predicted plan except PTV 70.4 , but the difference is only 0.5% which is still clinically acceptable. Conclusion: This study developed a new automated radiotherapy treatment planning system based on 3D dose prediction and 3D dose distribution-based optimization. It is a promising approach for realizing automated treatment planning in the future.

Background/Aims: Regular physical exercise can enhance resistance to many microbial infections. However, little is known about the mechanism underlying the changes in the immune system induced by regular exercise. Methods: We recruited members of a university badminton club as the regular exercise (RE) group and healthy sedentary students as the sedentary control (SC) group. We investigated the distribution of peripheral blood mononuclear cell (PBMC) subsets and functions in the two groups. Results: There were no significant differences in plasma cytokine levels between the RE and SC groups in the true resting state. However, enhanced levels of IFN-γ, TNF-α, IL-6, IFN-α and IL-12 were secreted by PBMCs in the RE group following microbial antigen stimulation, when compared to the SC group. In contrast, the levels of TNF-α and IL-6 secreted by PBMC in the RE group were suppressed compared with those in SC group following non-microbial antigen stimulation (concanavalin A or α-galactosylceramide). Furthermore, PBMC expression of TLR2, TLR7 and MyD88 was significantly increased in the RE group in response to microbial antigen stimulation. Conclusion: Regular exercise enhances immune cell activation in response to pathogenic stimulation leading to enhanced cytokine production mediated via the TLR signaling pathways.

We present a surfactant-free miniemulsion process for the preparation of monodisperse polystyrene@SiO2 nanoparticles with a well-defined core–shell structure. The strategy utilizes a silica precursor polymer, hyperbranched polyethoxy­siloxane (PEOS), as a sole miniemulsion stabilizer due to its water insolubility and at the same time pronounced amphiphilicity induced by hydrolysis at the oil/water interface. The core–shell particles are obtained by emulsifying a PEOS/styrene mixture in water and subsequent heating to initiate polymerization. As the polymerization proceeds, driven by osmotic pressure and incompatibility with polystyrene, PEOS macromolecules migrate continuously toward the oil/water interface where sol–gel reaction takes place. As soon as the polymerization is completed, PEOS is fully expelled from the polymer phase and is converted to silica on the polystyrene surface. This method allows an easy control of silica shell thickness by varying the PEOS concentration. The particle size, on the other hand, can be regulated not only by the shearing force but also by the pH of the aqueous medium. This process offers a new type of miniemulsion polymerization technique for the preparation of composite polymer particles that is facile, low cost, highly scalable, and environmentally friendly.

BackgroundThe aim of this study was to analyze the influence of volumetric changes of bladder and rectum filling on the 3D dose distribution in prostate cancer radiotherapy.MethodsA total of 314 cone-beam CT (CBCT) image data sets from 19 patients were enrolled in this study. For each CBCT, the bladder and rectum were contoured and volume sizes were normalized to those on their original CT. The daily delivered dose was recalculated on the CBCT images and the doses to bladder and rectum were investigated. Linear regression analysis was performed to identify the mean dose change of the volume change using SPSS 19.ResultsThe data show that the variances of the normalized volume of the bladder and the rectum are 0.13–0.58 and 0.12–0.50 respectively. The variances of V70Gy, V60Gy, V50Gy, V40Gy and V30Gy of bladder are bigger than those of rectum for 17 patients. The linear regression analysis indicates a 10 % increase in bladder volume will cause a 5.6 % (±4.9 %) reduction in mean dose (p <0.05).ConclusionsThe bladder’s volume change is more significant than that of the rectum for the prostate cancer patient. The rectum volume variations are not significant except for air bubbles, which change the shape and the position of the rectum. The bladder volume variations may cause dose changes proportionately. Monitoring the bladder’s volume before fractional treatment delivery will be crucial for accurate dose delivery.

Strong saturable absorption was observed in MoS2 nanoflowers, which were synthesized by a facile solvothermal method. A MoS2 nanoflower-based saturable absorber with a high modulation depth of 51.8% and a large saturable intensity of 275.5 GW cm(-2) was introduced to the application of passively Q-switched fiber laser generation. Stable passively Q-switched fiber laser pulses at 1.56 μm with a low threshold power of 16.10 mW, high signal-to-noise ratio of 52.5 dB and short pulse duration of 1.9 μs were obtained. More importantly, a high output power of 3.10 mW related to a large pulse energy of about 51.84 nJ can be attained at a very low pump power. The efficiency of the laser reaches 4.71%, which is larger than that of the prepared layered MoS2 and recently reported MoS2-based passively Q-switching operations. Such results imply that the MoS2 nanoflowers are an excellent candidate for a saturable absorber in passively Q-switched fiber lasers at a low pump intensity.

Due to image quality limitations, online Megavoltage cone beam CT (MV CBCT), which represents real online patient anatomy, cannot be used to perform adaptive radiotherapy (ART). In this study, we used a deep learning method, the cycle-consistent adversarial network (CycleGAN), to improve the MV CBCT image quality and Hounsfield-unit (HU) accuracy for rectal cancer patients to make the generated synthetic CT (sCT) eligible for ART. Forty rectal cancer patients treated with the intensity modulated radiotherapy (IMRT) were involved in this study. The CT and MV CBCT images of 30 patients were used for model training, and the images of the remaining 10 patients were used for evaluation. Image quality, autosegmentation capability and dose calculation capability using the autoplanning technique of the generated sCT were evaluated. The mean absolute error (MAE) was reduced from 135.84 ± 41.59 HU for the CT and CBCT comparison to 52.99 ± 12.09 HU for the CT and sCT comparison. The structural similarity (SSIM) index for the CT and sCT comparison was 0.81 ± 0.03, which is a great improvement over the 0.44 ± 0.07 for the CT and CBCT comparison. The autosegmentation model performance on sCT for femoral heads was accurate and required almost no manual modification. For the CTV and bladder, although modification was needed for autocontouring, the Dice similarity coefficient (DSC) indices were high, at 0.93 and 0.94 for the CTV and bladder, respectively. For dose evaluation, the sCT-based plan has a much smaller dose deviation from the CT-based plan than that of the CBCT-based plan. The proposed method solved a key problem for rectal cancer ART realization based on MV CBCT. The generated sCT enables ART based on the actual patient anatomy at the treatment position.

A novel and rapid method for simultaneous extraction and separation of the different polysaccharides from Semen Cassiae (SC) was developed by microwave-assisted aqueous two-phase extraction (MAATPE) in a one-step procedure. Using ethanol/ammonium sulfate system as a multiphase solvent, the effects of MAATPE on the extraction of polysaccharides from SC such as the composition of the ATPS, extraction time, temperature and solvent-to-material ratio were investigated by UV-vis analysis. Under the optimum conditions, the yields of polysaccharides were 4.49% for the top phase, 8.80% for the bottom phase and 13.29% for total polysaccharides, respectively. Compared with heating solvent extraction and ultrasonic assisted extraction, MAATPE exhibited the higher extraction yields in shorter time. Fourier-transform infrared spectra showed that two polysaccharides extracted from SC to the top and bottom phases by MAATPE were different from each other in their chemical structures. Through acid hydrolysis and PMP derivatization prior to HPLC, analytical results by indicated that a polysaccharide of the top phases was a relatively homogeneous homepolysaccharide composed of dominant gucose glucose while that of the bottom phase was a water-soluble heteropolysaccharide with multiple components of glucose, xylose, arabinose, galactose, mannose and glucuronic acid. Molar ratios of monosaccharides were 95.13:4.27:0.60 of glucose: arabinose: galactose for the polysaccharide from the top phase and 62.96:14.07:6.67: 6.67:5.19:4.44 of glucose: xylose: arabinose: galactose: mannose: glucuronic acid for that from the bottom phase, respectively. The mechanism for MAATPE process was also discussed in detail. MAATPE with the aid of microwave and the selectivity of the ATPS not only improved yields of the extraction, but also obtained a variety of polysaccharides. Hence, it was proved as a green, efficient and promising alternative to simultaneous extraction of polysaccharides from SC.

Infection with human papillomavirus (HPV) is the main cause of cervical cancer, the principal cancer in women in most developing countries. Molecular epidemiologic evidence clearly indicates that certain types of HPV are the principal cause of invasive cervical cancer and cervical intraepithelial neoplasia. Comprehensive, high-throughput typing assays for HPV, however, are not currently available. By combining L1 consensus PCR and multiplex hybridization using a Luminex xMAP system-based suspension array, the authors developed a rapid high-throughput assay, the HPV DNA suspension array (HPV-SA), capable of simultaneously typing 26 HPVs, including 18 high-risk HPV genotypes and eight low-risk HPV genotypes. The performance of the HPV-SA applied to 26 synthetic oligonucleotide targets was evaluated. The HPV-SA system perfectly discriminated 18 high-risk HPV targets from eight low-risk HPV targets. To assess the clinical applicability of the assay, the HPV-SA was performed with 133 MY09/MY11 primer set-mediated PCR (MY-PCR)-positive clinical specimens; of the 133 samples, 121 were positive by HPV-SA. Both single and multiple types were easily identified. The authors believe that improvement of the assay may be useful for epidemiological studies, cancer-screening programmes, the monitoring of therapeutic interventions, and the evaluation of the efficacy of HPV vaccine trials.