Dosimetric comparison of intensity modulated radiotherapy and three-dimensional conformal radiotherapy in patients with gynecologic malignancies: a systematic review and meta-analysis

BACKGROUND: To quantitatively evaluate the safety and related-toxicities of intensity modulated radiotherapy (IMRT) dose–volume histograms (DVHs), as compared to the conventional three-dimensional conformal radiotherapy (3D-CRT), in gynecologic malignancy patients by systematic review of the related publications and meta-analysis. METHODS: Relevant articles were retrieved from the PubMed, Embase, and Cochrane Library databases up to August 2011. Two independent reviewers assessed the included studies and extracted data. Pooled average percent irradiated volumes of adjacent non-cancerous tissues were calculated and compared between IMRT and 3D-CRT for a range of common radiation doses (5-45Gy). RESULTS: In total, 13 articles comprised of 222 IMRT-treated and 233 3D-CRT-treated patients were included. For rectum receiving doses ≥30 Gy, the IMRT pooled average irradiated volumes were less than those from 3D-CRT by 26.40% (30 Gy, p = 0.004), 27.00% (35 Gy, p = 0.040), 37.30% (40 Gy, p = 0.006), and 39.50% (45 Gy, p = 0.002). Reduction in irradiated small bowel was also observed for IMRT-delivered 40 Gy and 45 Gy (by 17.80% (p = 0.043) and 17.30% (p = 0.012), respectively), as compared with 3D-CRT. However, there were no significant differences in the IMRT and 3D-CRT pooled average percent volumes of irradiated small bowel or rectum from lower doses, or in the bladder or bone marrow from any of the doses. IMRT-treated patients did not experience more severe acute or chronic toxicities than 3D-CRT-treated patients. CONCLUSIONS: IMRT-delivered high radiation dose produced significantly less average percent volumes of irradiated rectum and small bowel than 3D-CRT, but did not differentially affect the average percent volumes in the bladder and bone marrow

Integrative Analysis of Identifying Methylation-Driven Genes Signature Predicts Prognosis in Colorectal Carcinoma

BackgroundAberrant DNA methylation is a critical regulator of gene expression and plays a crucial role in the occurrence, progression, and prognosis of colorectal cancer (CRC). We aimed to identify methylation-driven genes by integrative epigenetic and transcriptomic analysis to predict the prognosis of CRC patients.MethodsMethylation-driven genes were selected for CRC using a MethylMix algorithm and LASSO regression screening strategy, and were further used to construct a prognostic risk-assessment model. The Cancer Genome Atlas (TCGA) database was obtained as the training set for both the screening of methylation-driven genes and the effect of genes signature on CRC prognosis. Then, the prognostic genes signature was validated in three independent expression arrays of CRC data from Gene Expression Omnibus (GEO).ResultsWe identified 143 methylation-driven genes, of which the combination of BATF, PHYHIPL, RBP1, and PNPLA4 expression levels was screened as a better prognostic model with the best area under the curve (AUC) (AUC = 0.876). Compared with patients in the low-risk group, CRC patients in the high-risk group had significantly poorer overall survival in the training set (HR = 2.184, 95% CI: 1.404–3.396, P < 0.001). Similar results were observed in the validation set. Moreover, VanderWeele’s mediation analysis indicated that the effect of methylation on prognosis was mediated by the levels of their expression (HRindirect = 1.473, P = 0.001, Proportion mediated, 69.10%).ConclusionsWe identified a four-gene prognostic signature by integrative analysis and developed a risk-assessment model that is significantly associated with patients’ survival. Methylation-driven genes might be a potential prognostic signature for CRC patients

Seismic Performance of Full-Scale Joints Composed by Concrete-Filled Steel Tube Column and Reinforced Concrete Beam with Steel Plate-Stud Connections

A concrete-filled steel tube (CFST) column has the advantages of high bearing capacity, high stiffness, and good ductility, while reinforced concrete (RC) structure systems are familiar to engineers. The combinational usage of CFST and RC components is playing an important role in contemporary projects. However, existing CFST column-RC beam joints are either too complex or have insufficient stiffness at the interface, so their practical engineering application has been limited. In this study, the results of a practical engineering project were used to develop two kinds of CFST column-RC beam joints that are connected by vertical or U-shaped steel plates and studs. The seismic performance of full-scale column-beam joints with a shear span ratio of 4 was examined when they were subjected to a low-cyclic reversed loading test. The results showed a plump load-displacement curve for the CFST column-RC beam joint connected by steel plates and studs, and the connection performance satisfied the building code. The beam showed a bending failure mode similar to that of traditional RC joints. The failure area was mainly concentrated outside the steel plate, and the plastic hinge moved outward from the ends of the beam. When the calculated cross section was set at the ends of the beam, the bending capacity of joints with the vertical or U-shaped steel plates and studs increased compared to the RC joint. However, when the calculated cross section was set to the failure area, the capacity was similar to that of the RC joint. The proposed joints showed increases in the energy dissipation, average energy dissipation coefficient, and ductility coefficient compared to the RC joint

Influence of Different Rotor Teeth Shapes on the Performance of Flux Switching Permanent Magnet Machines Used for Electric Vehicles

This paper investigated a 12-slot/11-pole flux switching permanent magnet (FSPM) machine used for electric vehicles (EVs). Five novel rotor teeth shapes are proposed and researched to reduce the cogging torque and torque ripple of the FSPM machine. These rotor teeth shapes are notched teeth, stepped teeth, eccentric teeth, combination of notched and stepped teeth, and combination of notched and eccentric teeth. They are applied on the rotor and optimized, respectively. The influences of different rotor teeth shapes on cogging torque, torque ripple and electromagnetic torque are analyzed by the 2-D finite-element method (FEM). Then, the performance of FSPMs with different rotor teeth shapes are compared and evaluated comprehensively from the points of view of cogging torque, torque ripple, electromagnetic torque, flux linkage, back electromotive force (EMF), and so on. The results show that the presented rotor teeth shapes, especially the combination of stepped and notched teeth, can greatly reduce the cogging torque and torque ripple with only slight changes in the average electromagnetic torque

Surface Roughness Prediction of Titanium Alloy during Abrasive Belt Grinding Based on an Improved Radial Basis Function (RBF) Neural Network

Titanium alloys have become an indispensable material for all walks of life because of their excellent strength and corrosion resistance. However, grinding titanium alloy is exceedingly challenging due to its pronounced material characteristics. Therefore, it is crucial to create a theoretical roughness prediction model, serving to modify the machining parameters in real time. To forecast the surface roughness of titanium alloy grinding, an improved radial basis function neural network model based on particle swarm optimization combined with the grey wolf optimization method (GWO-PSO-RBF) was developed in this study. The results demonstrate that the improved neural network developed in this research outperforms the classical models in terms of all prediction parameters, with a model-fitting R2 value of 0.919

Functional Networks of Reward and Punishment Processing and Their Molecular Profiles Predicting the Severity of Young Adult Drinking

Alcohol misuse is associated with altered punishment and reward processing. Here, we investigated neural network responses to reward and punishment and the molecular profiles of the connectivity features predicting alcohol use severity in young adults. We curated the Human Connectome Project data and employed connectome-based predictive modeling (CPM) to examine how functional connectivity (FC) features during wins and losses are associated with alcohol use severity, quantified by Semi-Structured Assessment for the Genetics of Alcoholism, in 981 young adults. We combined the CPM findings and the JuSpace toolbox to characterize the molecular profiles of the network connectivity features of alcohol use severity. The connectomics predicting alcohol use severity appeared specific, comprising less than 0.12% of all features, including medial frontal, motor/sensory, and cerebellum/brainstem networks during punishment processing and medial frontal, fronto-parietal, and motor/sensory networks during reward processing. Spatial correlation analyses showed that these networks were associated predominantly with serotonergic and GABAa signaling. To conclude, a distinct pattern of network connectivity predicted alcohol use severity in young adult drinkers. These “neural fingerprints” elucidate how alcohol misuse impacts the brain and provide evidence of new targets for future intervention

VXC-72R/ZrO2/GCE-Based Electrochemical Sensor for the High-Sensitivity Detection of Methyl Parathion

In this work, a carbon black (VXC-72R)/zirconia (ZrO2) nanocomposite-modified glassy carbon electrode (GCE) was designed, and a VXC-72R/ZrO2/GCE-based electrochemical sensor was successfully fabricated for the high-sensitivity detection of methyl parathion (MP). Electrochemical measurements showed that the VXC-72R/ZrO2/GCE-based electrochemical sensor could make full use of the respective advantages of the VXC-72R and ZrO2 nanoparticles to enhance the MP determination performance. The VXC-72R nanoparticles had high electrical conductivity and a large surface area, and the ZrO2 nanoparticles possessed a strong affinity to phosphorus groups, which could achieve good organophosphorus adsorption. On the basis of the synergistic effect generated from the interaction between the VXC-72R and ZrO2 nanoparticles, the VXC-72R/ZrO2/GCE-based electrochemical sensor could show excellent trace analysis determination performance. The low detection limit could reach up to 0.053 μM, and there was a linear concentration range of 1 μM to 100 μM. Such a high performance indicates that the VXC-72R/ZrO2/GCE-based electrochemical sensor has potential in numerous foreground applications

Sol-Gel Synthesis of Silicon-Doped Lithium Manganese Oxide with Enhanced Reversible Capacity and Cycling Stability

A series of silicon-doped lithium manganese oxides were obtained via a sol-gel process. XRD characterization results indicate that the silicon-doped samples retain the spinel structure of LiMn2O4. Electrochemical tests show that introducing silicon ions into the spinel structure can have a great effect on reversible capacity and cycling stability. When cycled at 0.5 C, the optimal Si-doped LiMn2O4 can exhibit a pretty high initial capacity of 140.8 mAh g−1 with excellent retention of 91.1% after 100 cycles, which is higher than that of the LiMn2O4, LiMn1.975Si0.025O4, and LiMn1.925Si0.075O4 samples. Moreover, the optimal Si-doped LiMn2O4 can exhibit 88.3 mAh g−1 with satisfactory cycling performance at 10 C. These satisfactory results are mainly contributed by the more regular and increased MnO6 octahedra and even size distribution in the silicon-doped samples obtained by sol-gel technology