Prediction of survival and analysis of prognostic factors for patients with AFP negative hepatocellular carcinoma: a population-based study.

PURPOSE: Hepatocellular carcinoma (HCC) has a poor prognosis, and alpha-fetoprotein (AFP) is widely used to evaluate HCC. However, the proportion of AFP-negative individuals cannot be disregarded. This study aimed to establish a nomogram of risk factors affecting the prognosis of patients with AFP-negative HCC and to evaluate its diagnostic efficiency. PATIENTS AND METHODS: Data from patients with AFP-negative initial diagnosis of HCC (ANHC) between 2004 and 2015 were collected from the Surveillance, Epidemiology, and End Results database for model establishment and validation. We randomly divided overall cohort into the training or validation cohort (7:3). Univariate and multivariate Cox regression analysis were used to identify the risk factors. We constructed nomograms with overall survival (OS) and cancer-specific survival (CSS) as clinical endpoint events and constructed survival analysis by using Kaplan-Meier curve. Also, we conducted internal validation with Receiver Operating Characteristic (ROC) analysis and Decision curve analysis (DCA) to validate the clinical value of the model. RESULTS: This study included 1811 patients (1409 men; 64.7% were Caucasian; the average age was 64 years; 60.7% were married). In the multivariate analysis, the independent risk factors affecting prognosis were age, ethnicity, year of diagnosis, tumor size, tumor grade, surgery, chemotherapy, and radiotherapy. The nomogram-based model related C-indexes were 0.762 (95% confidence interval (CI): 0.752-0.772) and 0.752 (95% CI: 0.740-0.769) for predicting OS, and 0.785 (95% CI: 0.774-0.795) and 0.779 (95% CI: 0.762-0.795) for predicting CSS. The nomogram model showed that the predicted death was consistent with the actual value. The ROC analysis and DCA showed that the nomogram had good clinical value compared with TNM staging. CONCLUSION: The age(HR:1.012, 95% CI: 1.006-1.018, P-value < 0.001), ethnicity(African-American: HR:0.946, 95% CI: 0.783-1.212, P-value: 0.66; Others: HR:0.737, 95% CI: 0.613-0.887, P-value: 0.001), tumor diameter(HR:1.006, 95% CI: 1.004-1.008, P-value < 0.001), year of diagnosis (HR:0.852, 95% CI: 0.729-0.997, P-value: 0.046), tumor grade(Grade 2: HR:1.124, 95% CI: 0.953-1.326, P-value: 0.164; Grade 3: HR:1.984, 95% CI: 1.574-2.501, P-value < 0.001; Grade 4: HR:2.119, 95% CI: 1.115-4.027, P-value: 0.022), surgery(Liver Resection: HR:0.193, 95% CI: 0.160-0.234, P-value < 0.001; Liver Transplant: HR:0.102, 95% CI: 0.072-0.145, P-value < 0.001), chemotherapy(HR:0.561, 95% CI: 0.471-0.668, P-value < 0.001), and radiotherapy(HR:0.641, 95% CI: 0.463-0.887, P-value:0.007) were independent prognostic factors for patients with ANHC. We developed a nomogram model for predicting the OS and CSS of patients with ANHC, with a good predictive performance.

Chemical fractionation and risk assessment of surface sediments in Luhun Reservoir, Luoyang city, China.

To understand the potential risks of heavy metals, including their bioavailability and toxicity, 15 surface sediment samples were collected from Luhun Reservoir in Luoyang city, China. Total concentrations and chemical fractions of Cd, Cr, Cu, Ni, Pb, and Zn were analyzed. Various rating methods were used to evaluate the degree, risk, and toxicity of the heavy metal pollution. Results showed that Cd and Pb were preferentially associated with exchangeable (55.77-69.76%) and reducible (53.54-69.43%) fractions, respectively, and therefore exhibited high potential availability. Cr (57.14-86.56%) and Ni (32.21-72.77%) occurred primarily in the residual fraction. Metal concentrations in the effective fraction of the sediment decreased in the order: Cd (96.32%) > Pb (91.61%) > Cu (64.54%) > Zn (57.23%) > Ni (41.51%) > Cr (21.68%). Risk assessment indicated that the risk for Cd is extremely high (62.96%); Cu, Pb, and Zn are ranked as medium risk. Based on the potential ecological risk index, these metals (especially Cd) showed higher potential risk near the dam region. Toxic unit values (2.89-6.05) in more than 60% of sediment sites exceeded a value of 4, and Pb had a relatively higher contribution (1.06-2.65). Cd and Pb are the main contaminants in sediments of Luhun Reservoir and should be paid more attention in the future.

Functional Site Discovery From Incomplete Training Data: A Case Study With Nucleic Acid-Binding Proteins.

Function annotation efforts provide a foundation to our understanding of cellular processes and the functioning of the living cell. This motivates high-throughput computational methods to characterize new protein members of a particular function. Research work has focused on discriminative machine-learning methods, which promise to make efficient, de novo predictions of protein function. Furthermore, available function annotation exists predominantly for individual proteins rather than residues of which only a subset is necessary for the conveyance of a particular function. This limits discriminative approaches to predicting functions for which there is sufficient residue-level annotation, e.g., identification of DNA-binding proteins or where an excellent global representation can be divined. Complete understanding of the various functions of proteins requires discovery and functional annotation at the residue level. Herein, we cast this problem into the setting of multiple-instance learning, which only requires knowledge of the protein's function yet identifies functionally relevant residues and need not rely on homology. We developed a new multiple-instance leaning algorithm derived from AdaBoost and benchmarked this algorithm against two well-studied protein function prediction tasks: annotating proteins that bind DNA and RNA. This algorithm outperforms certain previous approaches in annotating protein function while identifying functionally relevant residues involved in binding both DNA and RNA, and on one protein-DNA benchmark, it achieves near perfect classification.

Understanding Hygroscopic Nucleation of Sulfate Aerosols: Combination of Molecular Dynamics Simulation with Classical Nucleation Theory.

We present a combined molecular dynamics (MD) and classical nucleation theory (CNT) approach to address many issues regarding the nucleation of inorganic aerosols. By taking parameters from MD simulations, we find the CNT predicts fairly reasonable free-energy profiles for the hygroscopic nucleation of aerosols. Moreover, we find that the ionization of sulfates can play a key role in stabilizing aqueous clusters and that both the size of the critical nucleus and the nucleation barrier can be significantly lowered by the H2SO4 and NH4HSO4, whereas the effect of NH3 on nucleation is negligible. NH4HSO4 provides stronger enhancement effect to aerosol formation than H2SO4. In view of the consistency between the theoretical prediction and experimental observation, the combination of MD simulation and CNT appears to be a valuable approach to gain deeper understanding of how aerosol nucleation is affected by different chemical species.

Note: Development of a triple resonance pulse transformer based on magnetic core transformer.

In this paper, a triple resonance pulse transformer based on a magnetic core transformer is developed, which uses the first peak of the output voltage to charge the load capacitor. A compact magnetic core pulse transformer is developed, which uses an innovative bi-conical specific geometry. Based on this magnetic core pulse transformer, the triple resonance circuit is built by adding a tuning capacitor and a tuning inductor between this transformer and a pulse forming line (PFL). The tuning capacitor is designed to be an irregular coaxial capacitor with a capacitance of 70 pF and the tuning inductor is made as a single-layer air core cylindrical inductor. The experimental results indicate that the peak output voltage of the triple resonance pulse transformer is about 530 kV and the rise time is about 790 ns. The peak voltage across PFL is 1.6 times the peak voltage across the magnetic core transformer. It is feasible to develop a magnetic core pulse transformer into a triple resonance pulse transformer.

Microscopic Marangoni Flows Cannot Be Predicted on the Basis of Pressure Gradients.

A concentration gradient along a fluid-fluid interface can cause flow. On a microscopic level, this so-called Marangoni effect can be viewed as being caused by a gradient in the pressures acting on the fluid elements or as the chemical-potential gradients acting on the excess densities of different species at the interface. If the interface thickness can be ignored, all approaches should result in the same flow profile away from the interface. However, on a more microscopic scale, the different expressions result in different flow profiles, only one of which can be correct. Here we compare the results of direct nonequilibrium molecular dynamics simulations with the flows that are generated by pressure and chemical-potential gradients. We find that the approach based on the chemical-potential gradients agrees with the direct simulations, whereas the calculations based on the pressure gradients do not.

Tuning the structure and mechanical property of polymer nanocomposites by employing anisotropic nanoparticles as netpoints.

Introducing carbon nanotubes or graphene sheets into polymer matrices has received lots of scientific and technological attention. For the first time, we report a new kind of polymer nanocomposite (PNC) by means of employing anisotropic nanoparticles (NPs) as netpoints (referred to as an end-linked system), namely with NPs acting as netpoints to chemically connect the dual end-groups of each polymer chain to form a network. By taking advantage of this strategy, the anisotropic NPs can be uniformly distributed in the polymer matrix, with the NPs being separated via the connected polymer chains. And the separation distance between NPs, the stress-strain behavior and the dynamic hysteresis loss (HL) can be manipulated by varying the temperature and the polymer chain flexibility. Meanwhile, the physically mixed system is investigated by changing the interaction strength between polymer and NPs, and the temperature. It is emphasized that compared to the physically mixed system, the end-linked system which employs carbon nanotubes or graphene as netpoints possesses good thermal stability because of its thermodynamically stable morphology, exhibiting both excellent static and dynamic mechanical properties. These results help us to design and fabricate high performance and multi-functional PNCs filled with carbon nanotubes or graphene, facilitating the potentially large industrial application of these nanomaterials.

Development of a compact generator for gigawatt, nanosecond high-voltage pulses.

A compact generator producing 2.2-ns 1.5 GW high-voltage pulses was developed. The generator employed a 27.6 Ω, 0.9 ns pulse-forming-line (PFL), which was charged by an iron core transformer with a turn ratio of 2:33.5 and a coefficient of 0.94. A 1.2 µF, 20 kV capacitor and a hydrogen thyratron were used in the primary circuit. When the thyratron closed at 14.5 kV, 3.4% of the energy stored in the capacitor was delivered to the PFL in 850 ns, producing a peak voltage of up to ∼500 kV. In addition, the principle of triple resonance transformation was employed by adding a 50 pF tuning capacitor and a 1.15 mH inductor between the transformer and the PFL, which led to a significant reduction of the duration and peak value of the transformer voltage without reducing that in the PFL. Meanwhile, an adjustable self-break oil switch was applied. By using transmission lines with impedance overmatched to that of the PFL, the generator delivered a 512 kV pulse across an electron beam diode, generating radiation with a dose of 20 mR/pulse at 20 cm ahead of the diode. The generator provides an excellent ultra-short radiation pulse source for the studies on radiation physics.

Systematic Tuning and Multifunctionalization of Covalent Organic Polymers for Enhanced Carbon Capture.

Porous covalent polymers are attracting increasing interest in the fields of gas adsorption, gas separation, and catalysis due to their fertile synthetic polymer chemistry, large internal surface areas, and ultrahigh hydrothermal stabilities. While precisely manipulating the porosities of porous organic materials for targeted applications remains challenging, we show how a large degree of diversity can be achieved in covalent organic polymers by incorporating multiple functionalities into a single framework, as is done for crystalline porous materials. Here, we synthesized 17 novel porous covalent organic polymers (COPs) with finely tuned porosities, a wide range of Brunauer-Emmett-Teller (BET) specific surface areas of 430-3624 m(2) g(-1), and a broad range of pore volumes of 0.24-3.50 cm(3) g(-1), all achieved by tailoring the length and geometry of building blocks. Furthermore, we are the first to successfully incorporate more than three distinct functional groups into one phase for porous organic materials, which has been previously demonstrated in crystalline metal-organic frameworks (MOFs). COPs decorated with multiple functional groups in one phase can lead to enhanced properties that are not simply linear combinations of the pure component properties. For instance, in the dibromobenzene-lined frameworks, the bi- and multifunctionalized COPs exhibit selectivities for carbon dioxide over nitrogen twice as large as any of the singly functionalized COPs. These multifunctionalized frameworks also exhibit a lower parasitic energy cost for carbon capture at typical flue gas conditions than any of the singly functionalized frameworks. Despite the significant improvement, these frameworks do not yet outperform the current state-of-art technology for carbon capture. Nonetheless, the tuning strategy presented here opens up avenues for the design of novel catalysts, the synthesis of functional sensors from these materials, and the improvement in the performance of existing covalent organic polymers by multifunctionalization.

How Properties of Solid Surfaces Modulate the Nucleation of Gas Hydrate.

Molecular dynamics simulations were performed for CO2 dissolved in water near silica surfaces to investigate how the hydrophilicity and crystallinity of solid surfaces modulate the local structure of adjacent molecules and the nucleation of CO2 hydrates. Our simulations reveal that the hydrophilicity of solid surfaces can change the local structure of water molecules and gas distribution near liquid-solid interfaces, and thus alter the mechanism and dynamics of gas hydrate nucleation. Interestingly, we find that hydrate nucleation tends to occur more easily on relatively less hydrophilic surfaces. Different from surface hydrophilicity, surface crystallinity shows a weak effect on the local structure of adjacent water molecules and on gas hydrate nucleation. At the initial stage of gas hydrate growth, however, the structuring of molecules induced by crystalline surfaces are more ordered than that induced by amorphous solid surfaces.

Improving forecasting accuracy of medium and long-term runoff using artificial neural network based on EEMD decomposition.

Hydrological time series forecasting is one of the most important applications in modern hydrology, especially for the effective reservoir management. In this research, an artificial neural network (ANN) model coupled with the ensemble empirical mode decomposition (EEMD) is presented for forecasting medium and long-term runoff time series. First, the original runoff time series is decomposed into a finite and often small number of intrinsic mode functions (IMFs) and a residual series using EEMD technique for attaining deeper insight into the data characteristics. Then all IMF components and residue are predicted, respectively, through appropriate ANN models. Finally, the forecasted results of the modeled IMFs and residual series are summed to formulate an ensemble forecast for the original annual runoff series. Two annual reservoir runoff time series from Biuliuhe and Mopanshan in China, are investigated using the developed model based on four performance evaluation measures (RMSE, MAPE, R and NSEC). The results obtained in this work indicate that EEMD can effectively enhance forecasting accuracy and the proposed EEMD-ANN model can attain significant improvement over ANN approach in medium and long-term runoff time series forecasting.

A hybrid absorption-adsorption method to efficiently capture carbon.

Removal of carbon dioxide is an essential step in many energy-related processes. Here we report a novel slurry concept that combines specific advantages of metal-organic frameworks, ion liquids, amines and membranes by suspending zeolitic imidazolate framework-8 in glycol-2-methylimidazole solution. We show that this approach may give a more efficient technology to capture carbon dioxide compared to conventional technologies. The carbon dioxide sorption capacity of our slurry reaches 1.25 mol l(-1) at 1 bar and the selectivity of carbon dioxide/hydrogen, carbon dioxide/nitrogen and carbon dioxide/methane achieves 951, 394 and 144, respectively. We demonstrate that the slurry can efficiently remove carbon dioxide from gas mixtures at normal pressure/temperature through breakthrough experiments. Most importantly, the sorption enthalpy is only -29 kJ mol(-1), indicating that significantly less energy is required for sorbent regeneration. In addition, from a technological point of view, unlike solid adsorbents slurries can flow and be pumped. This allows us to use a continuous separation process with heat integration.

Contact line pinning and the relationship between nanobubbles and substrates.

We report a theoretical study of nanobubble stabilization on a substrate by contact line pinning. In particular, we predict the magnitude of the pinning force required to stabilize a nanobubble and the threshold values of the pinning force that the substrate can provide. We show that the substrate chemistry and the local structures of substrate heterogeneity together determine whether or not surface nanobubbles are stable. We find that for stable nanobubbles, the contact angles are independent of substrate chemistry as its effects are cancelled out by the pinning effect. This prediction is in agreement with available experimental data.

Cosolvent or antisolvent? A molecular view of the interface between ionic liquids and cellulose upon addition of another molecular solvent.

Ionic liquids (ILs) are promising nonderivatizing solvents for the dissolution of cellulose and lignin in biomass pretreatment processes, which are, however, retarded by sluggish dynamics. Recent investigations showed that cosolvents such as dimethyl sulfoxide (DMSO) can accelerate the dissolution dramatically. On the other hand, water is used as a common antisolvent to regenerate cellulose from solutions. To understand the co-/antisolvent effects in dissolving cellulose by ILs, we performed molecular dynamics simulations of the interfaces between an Iß cellulose crystal and different solvent systems, including ILs, DMSO, water, and mixed solvent systems. The density profiles and pair energy distributions (PEDs) show that the anions interact much more strongly with the cellulose surface than the cations, which is responsible for the dissolution of cellulose. It was found that the number of chloride ions in contact with cellulose does not cause the co-/antisolvent effect. In contrast, the cellulose-chloride PEDs are sensitive to the addition of molecular solvents, such as DMSO and water. Detailed analyses show that multiple hydrogen-bond (HB) patterns are formed between chloride and the hydroxyl groups of cellulose that are noticeably changed in the presence of DMSO or water. A combined analyses of both the PEDs and HB patterns can provide valuable information about the enhancement of cellulose dissolution. The simulation results in this work present useful knowledge for the design of solvent systems for dissolving cellulose or other types of biomass.

Semiconducting and conducting transition of covalent-organic polymers induced by defects.

The chemical doping method is often adopted to obtain metal-free conducting materials. To date, it is still a great challenge to controllably prepare metal-free semiconducting and conducting materials by tuning the inherent structure of a material. In this work, a class of novel one-dimensional (1D) covalent-organic polymer (COP) has been designed, whose cross-sections are triangular, tetragonal, pentagonal and hexagonal, and their electronic properties are explored. The tetragonal 1D COP exhibits unique phenomena in electronic properties, i.e. the tetragonal COPs with mono- or trilayer defects (odd defects) show semiconducting properties, while they become conductors for the two cases of non- or bilayer defects (even defects). This observation indicates that they comply with the characteristics of semiconducting and conducting switches induced by the odd-even defects. Therefore, we infer that for the tetragonal configuration, the odd-even defects could potentially manipulate the electrical behavior of the COP material. The discovery provides a new direction for the targeted synthesis of semiconducting and conducting materials by tuning the inherent structure of materials, which is entirely different from the chemical doping method yielding metal-free conducting materials.

Nucleation of the CO2 hydrate from three-phase contact lines.

Using molecular dynamics simulations on the microsecond time scale, we investigate the nucleation and growth mechanisms of CO(2) hydrates in a water/CO(2)/silica three-phase system. Our simulation results indicate that the CO(2) hydrate nucleates near the three-phase contact line rather than at the two-phase interfaces and then grows along the contact line to form an amorphous crystal. In the nucleation stage, the hydroxylated silica surface can be understand as a stabilizer to prolong the lifetime of adsorbed hydrate cages that interact with the silica surface by hydrogen bonding, and the adsorbed cages behave as the nucleation sites for the formation of an amorphous CO(2) hydrate. After nucleation, the nucleus grows along the three-phase contact line and prefers to develop toward the CO(2) phase as a result of the hydrophilic nature of the modified solid surface and the easy availability of CO(2) molecules. During the growth process, the population of sI cages in the formed amorphous crystal is found to increase much faster than that of sII cages, being in agreement with the fact that only the sI hydrate can be formed in nature for CO(2) molecules.

Tailoring of Pd-Pt bimetallic clusters with high stability for oxygen reduction reaction.

The composition-dependent equilibrium structure and thermal stability of Pd-Pt clusters with the size of 55 atoms, and CO, O, OH, and O(2) adsorption on these clusters have been studied using molecular simulation based on the Gupta empirical potential and density functional theory (DFT) calculations. It is found that Pd(43)Pt(12) with a three-shell onionlike structure (TS-cluster) exhibits the highest relative stability in both DFT and Gupta levels and also the highest melting point at the Gupta level among these Pd-Pt clusters. In addition, the Pd(43)Pt(12) TS-cluster possesses the weakest CO, O, OH, and O(2) adsorption strength, compared to the Pt(55), Pd(55), and Pd(13)Pt(42) clusters, indicating good catalytic activities toward the oxygen reduction reaction (ORR) among these Pd-Pt clusters considered. We expect that this kind of DFT-guided strategy by controlling the composition could provide a simple way for possibly searching new electrocatalysts.

Rupture kinetics of liquid bridges during a pulling process: a kinetic density functional theory study.

Capillary bridge is a common phenomenon in nature and can significantly contribute to the adhesion of biological and artificial micro- and nanoscale objects. Especially, it plays a crucial role in the operation of atomic force microscopy (AFM) and influences in the measured force. In the present work, we study the rupture kinetics and transition pathways of liquid bridges connecting an AFM tip and a flat substrate during a process of pulling the tip off. Depending on thermodynamic conditions and the tip velocity, two regimes corresponding to different transition pathways are identified. In the single-bridge regime, the initial equilibrium bridge persists as a single one during the pulling process until the liquid bridge breaks. While, in the multibridge regime the stretched liquid bridge transforms into an intermediate state with a collection of slender liquid bridges, which then break gradually during the pulling process. Moreover, the critical rupture distance at which the bridges break changes with the tip velocity and thermodynamic conditions, and its maximum value occurs near the boundary between the single-bridge regime and the multibridge regime, where the longest range capillary force is produced. In this work, the effects of tip velocity, tip size, tip-fluid interaction, and humidity on rupture kinetics and transition pathways are also systematically studied.

Microsecond molecular dynamics simulations of the kinetic pathways of gas hydrate formation from solid surfaces.

In this paper, we report microsecond molecular dynamics simulations of the kinetic pathway of CO(2) hydrate formation triggered by hydroxylated silica surfaces. Our simulation results show that the nucleation of the CO(2) hydrate is a three-stage process. First, an icelike layer is formed closest to the substrates on the nanosecond scale. Then, on the submicrosecond timescale, a thin layer with intermediate structure is induced to compensate for the structure mismatch between the icelike layer and the final stable CO(2) hydrate. Finally, on the microsecond timescale, the nucleation of the first CO(2) hydrate motif layer is generated from the intermediate structure that acts as nucleation seeds. We also address the effects of the distance between two surfaces.