Artificial intelligence for the prevention and prediction of colorectal neoplasms

BACKGROUND

Colonoscopy is a useful as a cancer screening test. However, in countries with limited medical resources, there are restrictions on the widespread use of endoscopy. Non-invasive screening methods to determine whether a patient requires a colonoscopy are thus desired. Here, we investigated whether artificial intelligence (AI) can predict colorectal neoplasia.

METHODS

We used data from physical exams and blood analyses to determine the incidence of colorectal polyp. However, these features exhibit highly overlapping classes. The use of a kernel density estimator (KDE)-based transformation improved the separability of both classes.

RESULTS

Along with an adequate polyp size threshold, the optimal machine learning (ML) models' performance provided 0.37 and 0.39 Matthews correlation coefficient (MCC) for the datasets of men and women, respectively. The models exhibit a higher discrimination than fecal occult blood test with 0.047 and 0.074 MCC for men and women, respectively.

CONCLUSION

The ML model can be chosen according to the desired polyp size discrimination threshold, may suggest further colorectal screening, and possible adenoma size. The KDE feature transformation could serve to score each biomarker and background factors (health lifestyles) to suggest measures to be taken against colorectal adenoma growth. All the information that the AI model provides can lower the workload for healthcare providers and be implemented in health care systems with scarce resources. Furthermore, risk stratification may help us to optimize the efficiency of resources for screening colonoscopy.

Efficient Search for Energetically Favorable Molecular Conformations against Metastable States via Gray-Box Optimization

In order to accurately understand and estimate molecular properties, finding energetically favorable molecular conformations is the most fundamental task for atomistic computational research on molecules and materials. Geometry optimization based on quantum chemical calculations has enabled the conformation prediction of arbitrary molecules, including de novo ones. However, it is computationally expensive to perform geometry optimizations for enormous conformers. In this study, we introduce the gray-box optimization (GBO) framework, which enables optimal control over the entire geometry optimization process, among multiple conformers. Algorithms designed for GBO roughly estimate energetically preferable conformers during their geometry optimization iterations. They then preferentially compute promising conformers. To evaluate the performance of the GBO framework, we applied it to a test set consisting of seven dipeptides and mycophenolic acid to determine their stable conformations at the density functional theory level. We thus preferentially obtained energetically favorable conformations. Furthermore, the computational costs required to find the most stable conformation were significantly reduced (approximately 1% on average, compared to the naive approach for the dipeptides).

Anisotropic Poisson Effect and Deformation-Induced Fluorescence Change of Elastic 9,10-Dibromoanthracene Single Crystals

Elastic organic crystals have attracted considerable attention as next-generation flexible smart materials. However, the detailed information on both molecular packing change and macroscopic mechanical crystal deformations upon applied stress is still insufficient. Herein, we report that fluorescent single crystals of 9,10-dibromoanthracene are elastically bendable and stretchable, which allows a detailed investigation of the deformation behavior. We clearly observed a Poisson effect for the crystal, where the short axes (b and c-axes) of the crystal are contracted upon elongation along the long axis (a-axis). Moreover, we found that the Poisson's ratios along the b-axis and c-axis are largely different. Theoretical molecular simulation suggests that the tilting motion of the anthracene may be responsible for the large deformation along the c-axis. Spatially resolved photoluminescence (PL) measurement of the bent elastic crystals reveals that the PL spectra at the outer (elongated), central (neutral), and inner (contracted) sides are different from each other.

New Insights in the Natural Organic Matter Fouling Mechanism of Polyamide and Nanocomposite Multiwalled Carbon Nanotubes-Polyamide Membranes

Polyamide (PA) membranes comprise most of the reverse osmosis membranes currently used for desalination and water purification. However, their fouling mechanisms with natural organic matter (NOM) is still not completely understood. In this work, we studied three different types of PA membranes: a laboratory made PA, a commercial PA, and a multiwalled carbon nanotube (CNT-PA nanocomposite membrane during cross-flow measurements by NaCl solutions including NOM, humic acid (HA), or alginate, respectively). Molecular dynamic simulations were also used to understand the fouling process of NOM down to its molecular scale. Low molecular weight humic acid binds to the surface cavities on the PA structures that leads to irreversible adsorption induced by the high surface roughness. In addition, the larger alginate molecules show a different mechanism, due to their larger size and their ability to change shape from the globule type to the uncoiled state. Specifically, alginate molecules either bind through Ca²⁺ bridges or they uncoil and spread on the surface. This work shows that carbon nanotubes can help to decrease roughness and polymer mobility on the surfaces of the membranes at the molecular scale, which represents a novel method to design antifouling membranes.

A Simple Model for Relative Energies of All Fullerenes Reveals the Interplay between Intrinsic Resonance and Structural Deformation Effects in Medium-Sized Fullerenes

Fullerenes are sheets of sp² carbon atoms wrapped around to form spheres. With this simple consideration, we have in the present study devised and (with over 3600 DFT data points) successfully validated a simple model, termed R+D, for estimating the relative energies of fullerenes. This model contains a resonance component to account for the intrinsic differences between the π-energies of different fullerenes, and a deformation component for treating the distortions from planarity. Notably, we find that both terms (and they alone) are required to obtain good relative energies, which lends support to the formulation of the R+D model. An interesting finding is that for some medium-sized IPR fullerenes, their isomers show similar variations in the two components. We deduce that these fullerenes may represent a good opportunity for tuning molecular properties for practical applications. We hope that the promising results of the present study will encourage further investigations into fullerenes from a fundamental perspective.

From Linear to Foldamer and Assembly: Hierarchical Transformation of a Coplanar Conjugated Polymer into a Microsphere

Despite the coplanar structure, a conjugated alternating copolymer forms amorphous, well-defined microspheres without π-stacked crystalline domains. Here, we gain insights into the mechanism of how the coplanar conjugated polymer forms amorphous microspheres by means of spectroscopic studies on the assembly/disassembly processes. The difference of the spectral profiles of photoabsorption and photoluminescence with varying solvent/nonsolvent composition clarifies that stepwise assembly takes place through the microsphere formation; [1] intrapolymer linear-to-folding transformation upon diffusion of polar nonsolvent and [2] interpolymer assembly of the foldamers upon further addition of the nonsolvent to form microspheres. As shown in various biopolymers such as proteins and DNA, such stepwise folding and assembly behaviors of conjugated polymers from primary to secondary and tertiary structure open a new way to create transformable functional materials.

MPI/OpenMP hybrid parallel algorithm for resolution of identity second-order Møller-Plesset perturbation calculation of analytical energy gradient for massively parallel multicore supercomputers

A massively parallel algorithm of the analytical energy gradient calculations based the resolution of identity Møller-Plesset perturbation (RI-MP2) method from the restricted Hartree-Fock reference is presented for geometry optimization calculations and one-electron property calculations of large molecules. This algorithm is designed for massively parallel computation on multicore supercomputers applying the Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) hybrid parallel programming model. In this algorithm, the two-dimensional hierarchical MP2 parallelization scheme is applied using a huge number of MPI processes (more than 1000 MPI processes) for acceleration of the computationally demanding O(N⁵ ) step such as calculations of occupied-occupied and virtual-virtual blocks of MP2 one-particle density matrix and MP2 two-particle density matrices. The new parallel algorithm performance is assessed using test calculations of several large molecules such as buckycatcher C₆₀ @C₆₀ H₂₈ (144 atoms, 1820 atomic orbitals (AOs) for def2-SVP basis set, and 3888 AOs for def2-TZVP), nanographene dimer (C₉₆ H₂₄ )₂ (240 atoms, 2928 AOs for def2-SVP, and 6432 AOs for cc-pVTZ), and trp-cage protein 1L2Y (304 atoms and 2906 AOs for def2-SVP) using up to 32,768 nodes and 262,144 central processing unit (CPU) cores of the K computer. The results of geometry optimization calculations of trp-cage protein 1L2Y at the RI-MP2/def2-SVP level using the 3072 nodes and 24,576 cores of the K computer are presented and discussed to assess the efficiency of the proposed algorithm. © 2017 Wiley Periodicals, Inc.

Massively parallel algorithm and implementation of RI-MP2 energy calculation for peta-scale many-core supercomputers

A new parallel algorithm and its implementation for the RI-MP2 energy calculation utilizing peta-flop-class many-core supercomputers are presented. Some improvements from the previous algorithm (J. Chem. Theory Comput. 2013, 9, 5373) have been performed: (1) a dual-level hierarchical parallelization scheme that enables the use of more than 10,000 Message Passing Interface (MPI) processes and (2) a new data communication scheme that reduces network communication overhead. A multi-node and multi-GPU implementation of the present algorithm is presented for calculations on a central processing unit (CPU)/graphics processing unit (GPU) hybrid supercomputer. Benchmark results of the new algorithm and its implementation using the K computer (CPU clustering system) and TSUBAME 2.5 (CPU/GPU hybrid system) demonstrate high efficiency. The peak performance of 3.1 PFLOPS is attained using 80,199 nodes of the K computer. The peak performance of the multi-node and multi-GPU implementation is 514 TFLOPS using 1349 nodes and 4047 GPUs of TSUBAME 2.5. © 2016 Wiley Periodicals, Inc.

A Series of Layered Assemblies of Hydrogen-Bonded, Hexagonal Networks of C3-Symmetric π-Conjugated Molecules: A Potential Motif of Porous Organic Materials

Hydrogen-bonded porous organic crystals are promising candidates for functional organic materials due to their easy construction and flexibility arising from reversible bond formation-dissociation. However, it still remains challenging to form porous materials with void spaces that are well-controlled in size, shape, and multiplicity because even well-designed porous frameworks often fail to generate pores within the crystal due to unexpected disruption of hydrogen bonding networks or interpenetration of the frameworks. Herein, we demonstrate that a series of C3-symmetric π-conjugated planar molecules (Tp, T12, T18, and Ex) with three 4,4'-dicarboxy-o-terphenyl moieties in their periphery can form robust hydrogen-bonded hexagonal networks (H-HexNets) with dual or triple pores and that the H-HexNets stack without interpenetration to yield a layered assembly of H-HexNet (LA-H-HexNet) with accessible volumes up to 59%. Specifically, LA-H-HexNets of Tp and T12 exhibit high crystallinity and permanent porosity after desolvation (activation): SABET = 788 and 557 m(2) g(-1), respectively, based on CO2 sorption at 195 K. We believe that the present design principle can be applied to construct a wide range of two-dimensional noncovalent organic frameworks (2D-nCOFs) and create a pathway to the development of a new class of highly porous functional materials.

An immunohistological study of the integration at the bone-tendon interface after reconstruction of the anterior cruciate ligament in rabbits

We studied bone-tendon healing using immunohistochemical methods in a rabbit model.

Reconstruction of the anterior cruciate ligament was undertaken using semitendinosus tendon in 20 rabbits. Immunohistochemical evaluations were performed at one, two, four and eight weeks after the operation. The expression of CD31, RAM-11, VEGF, b-FGF, S-100 protein and collagen I, II and III in the bone-tendon interface was very similar to that in the endochondral ossification. Some of the type-III collagen in the outer layer of the graft, which was deposited at a very early phase after the operation, was believed to have matured into Sharpey-like fibres. However, remodelling of the tendon grafted into the bone tunnel was significantly delayed when compared with this ossification process. To promote healing, we believe that it is necessary to accelerate remodelling of the tendon, simultaneously with the augmentation of the ossification.

Energy density analysis of cluster size dependence of surface-molecule interactions: H2, C2H2, C2H4, and CO adsorption onto Si(100)-(2×1) surface

Adsorption of H2, C2H2, C2H4, and CO onto a Si(100)-(2x1) surface has been treated theoretically using Si(12n - 3)H(8n + 4) (n = 1-4) clusters. The energy density analysis (EDA) proposed by Nakai has been adopted to examine surface-molecule interactions for different cluster sizes. EDA results for the largest model cluster Si45H36 have shown that the adsorption-induced energy density variation in Si atoms decays with distance from the adsorption site. Analysis of this decay, which can be carried out using the EDA technique, is important because it enables verification of the reliability of the model cluster used. In the cases of H2, C2H2, C2H4, and CO adsorption onto the Si(100)-(2x1) surface, it is found that at least a Si21H20 cluster is necessary to treat the surface-molecule interaction with chemical accuracy.