Multi-omics and Multi-VOIs to predict esophageal fistula in esophageal cancer patients treated with radiotherapy.

OBJECTIVE: This study aimed to develop a prediction model for esophageal fistula (EF) in esophageal cancer (EC) patients treated with intensity-modulated radiation therapy (IMRT), by integrating multi-omics features from multiple volumes of interest (VOIs). METHODS: We retrospectively analyzed pretreatment planning computed tomographic (CT) images, three-dimensional dose distributions, and clinical factors of 287 EC patients. Nine groups of features from different combination of omics [Radiomics (R), Dosiomics (D), and RD (the combination of R and D)], and VOIs [esophagus (ESO), gross tumor volume (GTV), and EG (the combination of ESO and GTV)] were extracted and separately selected by unsupervised (analysis of variance (ANOVA) and Pearson correlation test) and supervised (Student T test) approaches. The final model performance was evaluated using five metrics: average area under the receiver-operator-characteristics curve (AUC), accuracy, precision, recall, and F1 score. RESULTS: For multi-omics using RD features, the model performance in EG model shows: AUC, 0.817 ± 0.031; 95% CI 0.805, 0.825; p < 0.001, which is better than single VOI (ESO or GTV). CONCLUSION: Integrating multi-omics features from multi-VOIs enables better prediction of EF in EC patients treated with IMRT. The incorporation of dosiomics features can enhance the model performance of the prediction.

Polarizability characteristics of twisted bilayer graphene quantum dots in the absence of periodic moiré potential.

Recent studies have documented a rich phenomenology in twisted bilayer graphene (TBG), which is significantly relevant to interlayer electronic coupling, in particular to the cases under an applied electric field. While polarizability measures the response of electrons against applied fields, this work adopts a unique strategy of decomposing global polarizability into distributional contributions to access the interlayer polarization in TBG, as a function of varying twisting angles (θ). Through the construction of a model of twisted graphene quantum dots, we assess distributional polarizability at the first-principles level. Our findings demonstrate that the polarizability perpendicular to the graphene plates can be decomposed into intralayer dipoles and interlayer charge-transfer (CT) components, the latter of which provides an explicit measurement of the interlayer coupling strength and charge transfer potential. Our analysis further reveals that interlayer polarizability dominates the polarizability variation during twisting. Intriguingly, the largest interlayer polarizability and CT driven by an external field occur in the misaligned structures with a size-dependent small angle corresponding to the first appearance of AB stacking, rather than the well-recognized Bernal structures. A derived equation is then employed to address the size dependence on the angle corresponding to the largest values in interlayer polarizability and CT. Our investigation not only characterizes the CT features in the interlayer polarizability of TBG quantum dots, but also sheds light on the existence of the strongest interlayer coupling and charge transfer at small twist angles in the presence of an external electric field, thereby providing a comprehensive understanding of the novel properties of graphene-based nanomaterials.

A novel automated planning approach for multi-anatomical sites cancer in Raystation treatment planning system.

PURPOSE: To develop an automated planning approach in Raystation and evaluate its feasibility in multiple clinical application scenarios. METHODS: An automated planning approach (Ruiplan) was developed by using the scripting platform of Raystation. Radiotherapy plans were re-generated both automatically by using Ruiplan and manually. 60 patients, including 20 patients with nasopharyngeal carcinoma (NPC), 20 patients with esophageal carcinoma (ESCA), and 20 patients with rectal cancer (RECA) were retrospectively enrolled in this study. Dosimetric and planning efficiency parameters of the automated plans (APs) and manual plans (MPs) were statistically compared. RESULTS: For target coverage, APs yielded superior dose homogeneity in NPC and RECA, while maintaining similar dose conformity for all studied anatomical sites. For OARs sparing, APs led to significant improvement in most OARs sparing. The average planning time required for APs was reduced by more than 43% compared with MPs. Despite the increased monitor units (MUs) for NPC and RECA in APs, the beam-on time of APs and MPs had no statistical difference. Both the MUs and beam-on time of APs were significantly lower than that of MPs in ESCA. CONCLUSIONS: This study developed a new automated planning approach, Ruiplan, it is feasible for multi-treatment techniques and multi-anatomical sites cancer treatment planning. The dose distributions of targets and OARs in the APs were similar or better than those in the MPs, and the planning time of APs showed a sharp reduction compared with the MPs. Thus, Ruiplan provides a promising approach for realizing automated treatment planning in the future.

Lung Subregion Partitioning by Incremental Dose Intervals Improves Omics-Based Prediction for Acute Radiation Pneumonitis in Non-Small-Cell Lung Cancer Patients.

Purpose: To evaluate the effectiveness of features obtained from our proposed incremental-dose-interval-based lung subregion segmentation (IDLSS) for predicting grade ≥ 2 acute radiation pneumonitis (ARP) in lung cancer patients upon intensity-modulated radiotherapy (IMRT). (1) Materials and Methods: A total of 126 non-small-cell lung cancer patients treated with IMRT were retrospectively analyzed. Five lung subregions (SRs) were generated by the intersection of the whole lung (WL) and five sub-regions receiving incremental dose intervals. A total of 4610 radiomics features (RF) from pre-treatment planning computed tomographic (CT) and 213 dosiomics features (DF) were extracted. Six feature groups, including WL-RF, WL-DF, SR-RF, SR-DF, and the combined feature sets of WL-RDF and SR-RDF, were generated. Features were selected by using a variance threshold, followed by a Student t-test. Pearson's correlation test was applied to remove redundant features. Subsequently, Ridge regression was adopted to develop six models for ARP using the six feature groups. Thirty iterations of resampling were implemented to assess overall model performance by using the area under the Receiver-Operating-Characteristic curve (AUC), accuracy, precision, recall, and F1-score. (2) Results: The SR-RDF model achieved the best classification performance and provided significantly better predictability than the WL-RDF model in training cohort (Average AUC: 0.98 ± 0.01 vs. 0.90 ± 0.02, p < 0.001) and testing cohort (Average AUC: 0.88 ± 0.05 vs. 0.80 ± 0.04, p < 0.001). Similarly, predictability of the SR-DF model was significantly stronger than that of the WL-DF model in training cohort (Average AUC: 0.88 ± 0.03 vs. 0.70 ± 0.030, p < 0.001) and in testing cohort (Average AUC: 0.74 ± 0.08 vs. 0.65 ± 0.06, p < 0.001). By contrast, the SR-RF model significantly outperformed the WL-RF model only in the training set (Average AUC: 0.93 ± 0.02 vs. 0.85 ± 0.03, p < 0.001), but not in the testing set (Average AUC: 0.79 ± 0.05 vs. 0.77 ± 0.07, p = 0.13). (3) Conclusions: Our results demonstrated that the IDLSS method improved model performance for classifying ARP with grade ≥ 2 when using dosiomics or combined radiomics-dosiomics features.

Interfacial interaction-driven rheological properties of quartz nanofluids from molecular dynamics simulations and density functional theory calculations.

Correlations of the shear viscosity of quartz nanofluids with particle concentration, particle size, and temperature were investigated with molecular dynamics simulations and density functional theory (DFT) calculations. A new understanding to the experimentally concluded correlations was addressed in terms of microscopic particle-water interfacial interaction in three aspects. First, the viscosity of quartz nanofluids at different particle concentrations, particle sizes, and temperatures were simulated using the equilibrium molecular dynamics simulations method to reproduce the experimental observations. At the same particle size, the nanofluid viscosity decreases significantly with temperature and increases with nanoparticle volume concentration, and at the same volume concentration, the nanofluid viscosity increases with the decrease of particle size. Second, DFT calculations confirm a stronger particle-water interaction than that among water molecules. The important role of particle-water interaction in the viscosity determination of nanofluids was revealed. Finally, a correlation was proposed to fit the simulated results and compared with earlier two-parameter correlations. One parameter in the correlation is indeed a constant, while the other is a function of SiO2-water interaction energy. Our study proposes a physical basis for the experimentally concluded correlations on the viscosity of nanofluids.

Improvement Using Planomics Features on Prediction and Classification of Patient-Specific Quality Assurance Using Head and Neck Volumetric Modulated Arc Therapy Plan.

Purpose: This study aimed to evaluate the utility of a new plan feature (planomics feature) for predicting the results of patient-specific quality assurance using the head and neck (H&N) volumetric modulated arc therapy (VMAT) plan. Methods: One hundred and thirty-one H&N VMAT plans in our institution from 2019 to 2021 were retrospectively collected. Dosimetric verification for all plans was carried out using the portal dosimetry system integrated into the Eclipse treatment planning system based on the electronic portal imaging devices. Gamma passing rates (GPR) were analyzed using three gamma indices of 3%/3 mm, 3%/2 mm, and 2%/2 mm with a 10% dose threshold. Forty-eight conventional features affecting the dose delivery accuracy were used in the study, and 2,476 planomics features were extracted based on the radiotherapy plan file. Three prediction and classification models using conventional features (CF), planomics features (PF), and hybrid features (HF) combining two sets of features were constructed by the gradient boosting regressor (GBR) and Ridge classifier for each GPR of 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. The absolute prediction error (APE) and the area under the curve (AUC) were adopted for assessing the performance of prediction and classification models. Results: In the GPR prediction, the average APE of the models using CF, PF, and HF was 1.3 ± 1.2%/3.6 ± 3.0%, 1.7 ± 1.5%/3.8 ± 3.5%, and 1.1 ± 1.0%/4.1 ± 3.1% for 2%/2 mm; 0.7 ± 0.6%/2.0 ± 2.0%, 1.0±1.1%/2.2 ± 1.8%, and 0.6 ± 0.6%/2.2 ± 1.9% for 3%/2 mm; and 0.4 ± 0.3%/1.2 ± 1.2%, 0.4±0.5%/1.3 ± 1.0%, and 0.3±0.3%/1.2 ± 1.1% for 3%/3 mm, respectively. In the regression prediction, three models give a similar modeling performance for predicting the GPR. The classification results were 0.67 ± 0.03/0.66 ± 0.07, 0.77 ± 0.03/0.73 ± 0.06, and 0.78 ± 0.02/0.75 ± 0.04 for 3%/3 mm, respectively. For 3%/2 mm, the AUCs of the training and testing cohorts were 0.64 ± 0.03/0.62 ± 0.07, 0.70 ± 0.03/0.67 ± 0.06, and 0.75 ± 0.03/0.71 ± 0.07, respectively, and for 2%/2 mm, the average AUCs of the training and testing cohorts were 0.72 ± 0.03/0.72 ± 0.06, 0.78 ± 0.04/0.73 ± 0.07, and 0.81 ± 0.03/0.75 ± 0.06, respectively. In the classification, the PF model has a better classification performance than the CF model. Moreover, the HF model provides the best result among the three classifications models. Conclusions: The planomics features can be used for predicting and classifying the GPR results and for improving the model performance after combining the conventional features for the GPR classification.

Optical absorption of warped nanographenes tuned by five- and seven-membered carbon rings.

The introduction of multiple carbon rings is one of the common ways for graphene modification. Starting from warped C80H30 nanographene, which consists of a number of six- and seven-membered carbon rings (C6 and C7) centering at a five-membered carbon ring (C5), we explored the structure and property variations of its derivatives in which their C7 rings were gradually replaced with C6 rings. With reducing number of C7 rings, their curved boundary with the C6 rings becomes flat until a bowl-like structure is formed when all the C7 rings disappear. The optical absorption spectra vary accordingly. Both the α-bands and the maximum absorption bands in the visible region are related to the number and location of the C7 rings. Further analysis of the excited states of the C80H30 derivatives, as well as on the designed model systems, revealed that the C7 rings affect the electron excitations in two ways. In addition to their participation in electronic transitions, they control the composition of molecular orbitals that are involved in the excitations. The highest occupied molecular orbitals are mainly contributed by atoms on the C6 and C7 rings, while the lowest unoccupied molecular orbitals by atoms on the C5 and C6 rings. Our study sheds some light on how the multiple carbon rings affect the optical absorption of nanographenes and provides information for the preparation of nanographenes with tunable structural and optical properties.

A study of optical absorption of cysteine-capped CdSe nanoclusters using first-principles calculations.

Understanding the size-dependent structures and properties of ligand-capped nanoclusters in solvent is of particular interest for the design, synthesis and application of II-VI colloidal QDs. Using DFT and TDDFT calculations, we studied the structure and optical property evolution of the cysteine-capped (CdSe)N clusters of N = 1-10, 13, 16 and 19 in gas, toluene, water and alkaline aqueous solution, and made a comparison with their corresponding bare clusters. The cysteine binds with (CdSe)Nvia several patterns depending on the medium they exist in, affecting the cluster structures and in consequence their optical absorption. In general, the absorption bands of (CdSe)N blueshift when cysteine is added, and the shift varies with the interaction strength between the cluster and the ligand, and the dielectric constant of the solvent. However, bare clusters retain their size sensitivity, in particular the redshift trend with increasing cluster size, and some similarity was noted for the optical absorption of the bare and ligated clusters regardless of the gas or solvent media. Population analysis reveals that the excitations are mainly from orbitals distributing on the (CdSe)N part, while the ligand is negligibly involved in the excitations. This is an important feature for the II-VI QDs as biosensors with which the information of biomolecules is detected from the size dependent optical absorption or emission of the QDs other than the biomolecules.

First-principles study of O2 activation on ligand-protected Au32 clusters.

Poly(N-vinyl-2-pyrrolidone) (PVP) is often used to protect active Au clusters from coalescence. The influences of PVP on the O2 adsorption on Au32 clusters were investigated using density functional theory calculations. Various low-lying structures of O2:Au32 and O2:Au32:PVP complexes, in which the Au32 is either neutral or anionic and the O2 is either molecular or dissociative, were identified. The PVP influences were evaluated in terms of the changes in geometry, adsorption energy, charge redistribution, spin density, and density of states upon PVP pre-adsorption. Our calculations reveal that PVP weakly adsorbs on the cluster surface, with rather small changes in the structural, geometrical and electronic properties that are relevant to the O2 activation. The activity of neutral or anionic Au32 towards O2 is kept or slightly enhanced by PVP because of the cooperative adsorption of PVP and O2. This is the structural basis of choosing PVP as the protective ligand for Au clusters.

First-principles study of ammonium ions and their hydration in montmorillonites.

Density functional theory calculations were performed to investigate the adsorption and hydration of an ammonium ion (NH4(+)) confined in the interlayer space of montmorillonites (MMT). NH4(+) is trapped in the six-oxygen-ring on the internal surface and forms a strong binding with the surface O atoms. The hydration of NH4(+) is affected significantly by the surface. Water molecules prefer the surface sites, and do not bind with the NH4(+) unless enough water molecules are supplied. Moreover, the water molecules involved in NH4(+) hydration tend to bind with the surface simultaneously. The hydration energy increases with the intercalated water molecules, in contrast to that in gas phase. In addition, the hydration leads to the extension of MMT basal spacing.

Oriental schistosomiasis with neurological complications: case report.

We describe a case of cerebral schistosomiasis, caused by Asian (oriental) Schistosoma japonicum trematode blood flukes, in a young Chinese patient and its management. We also provide a brief update for physicians on the clinical features, diagnosis and treatment of schistosomiasis, with particular emphasis on neuroschistosomiasis, the most severe clinical outcome associated with this parasitic infection.