Coulomb-mediated antibunching of an electron pair surfing on sound.

Electron flying qubits are envisioned as potential information links within a quantum computer, but also promise-like photonic approaches-to serve as self-standing quantum processing units. In contrast to their photonic counterparts, electron-quantum-optics implementations are subject to Coulomb interactions, which provide a direct route to entangle the orbital or spin degree of freedom. However, controlled interaction of flying electrons at the single-particle level has not yet been established experimentally. Here we report antibunching of a pair of single electrons that is synchronously shuttled through a circuit of coupled quantum rails by means of a surface acoustic wave. The in-flight partitioning process exhibits a reciprocal gating effect which allows us to ascribe the observed repulsion predominantly to Coulomb interaction. Our single-shot experiment marks an important milestone on the route to realize a controlled-phase gate for in-flight quantum manipulations.

Enhancement of apatite formation on Ti-50Zr alloy in simulated body environment.

Ti-50Zr alloy is 2.5 times as strong as pure Ti and has a lower Young's modulus, making it a useful material for repairing bone and teeth. However, Ti-50Zr alloy has a limited ability to bond with bone in vivo. Under biological conditions, apatite formation at the surface of a Ti or alloy implant is necessary for its bonding with bone. Various approaches to surface modification have been proposed to impart bone-bonding ability to Ti-50Zr alloy; however, there remains a need for further improvements to the alloy's apatite-forming ability. Hence, in this study, we compared apatite formation at the surface of alloy substrates in simulated body fluid, after various surface treatments. Treatment with 5 M NaOH followed by 1 M CaCl2 was the most effective procedure, whereas a sample subjected to a hot water post-treatment formed less apatite. Notably, no apatite formed on samples treated with 10 M NaOH.

[A Case of Gastric Large-Cell Neuroendocrine Carcinoma Combined with Adenocarcinoma in the Cecum].

A 74-year-old man with anemia visited our department. Esophagogastroduodenoscopy showed a type 2 lesion from the angulus to the antrum. Histopathological findings indicated gastric neuroendocrine carcinoma. Colonoscopy showed a type 1 lesion at the cecum. Distal gastrectomy was performed with D1+lymph node dissection, Roux-en-Y reconstruction, and ileocecal resection with D3 lymph node dissection. The patient was pathologically diagnosed with large-cell neuroendocrine carcinoma in the stomach, pT4a(SE), med, INF a>>b-c, ly1-2, v1(SM, EVG), pN0, pM0, pStageⅡB, and adenocarcinoma (tub1>tub2)of the cecum, pT2(MP), ly1(HE), v1(EVG, SM), pN0, pM0, pStageⅠ. Postoperatively, he received oral S-1 as an adjuvant chemotherapy. His postoperative course was uneventful without any recurrence over 18 months.

Changes in the microvascular structure of mucosal squamous cell carcinoma of the esophagus and their significance in tumor progression.

BACKGROUND: To identify the clinical T stage by endoscopy is a major diagnostic goal for superficial esophageal squamous cell carcinoma (ESCC). The completion of a microvascular morphological study of mucosal lesions is necessary to optimize therapy. MATERIALS AND METHODS: Images of 197 intra-papillary capillary loops (IPCLs) captured by magnified endoscopy from 15 esophagectomy specimens were studied for their morphological features and IPCL dimensions. RESULTS: The microvascular morphology was classified into four basic major patterns: 1. spiral loop, 2. wide loop (WL), 3. globular (G) and 4. reticular pattern. The microvascular features and dimensions differed according to the depth of tumor invasion. Especially the mean bundle outline (IPCL diameter) showed significant changes as 20.02, 22.32, and 27.08 µm, respectively, for M1, M2 and M3, respectively (M1:M2 P < 0.05, M2:M3 P < 0.01). CONCLUSIONS: During tumor stage progression, a high-volume blood demand and cancer cell overgrowth to occupy the laminar propria mucosa (LPM) cause obvious elongation, thickening, branching, irregularity and deformity of the IPCL, which were characteristics of M3 lesions. The results of the present study support and can be applied with the current Japanese classification for improving the diagnostic accuracy, especially to differentiate between M2 and M3 lesions based on the endoscopic findings.

Efficient enumeration of stereoisomers of outerplanar chemical graphs using dynamic programming.

Exhaustive and nonredundant generation of stereoisomers of a chemical compound with a specified constitution is an important tool for molecular structure elucidation and molecular design. It is known that many chemical compounds have outerplanar graph structures. In this paper we deal with chemical compounds composed of carbon, hydrogen, oxygen, and nitrogen atoms whose graphical structures are outerplanar and consider stereoisomers caused only by asymmetry around carbon atoms. Based on dynamic programming, we propose an algorithm of generating all stereoisomers without duplication. We treat a given outerplanar graph as a graph rooted at its structural center. Our algorithm first recursively computes the number of stereoisomers of the subgraph induced by the descendants of each vertex and then constructs each stereoisomer by backtracking the process of computing the numbers of stereoisomers. Our algorithm correctly counts the number of stereoisomers in O(n) time and space and correctly enumerates all of the stereoisomers in O(n³) time per stereoisomer on average and in O(n) space, where n is the number of atoms in a given structure.

Automated anatomical labeling of bronchial branches extracted from CT datasets based on machine learning and combination optimization and its application to bronchoscope guidance.

This paper presents a method for the automated anatomical labeling of bronchial branches extracted from 3D CT images based on machine learning and combination optimization. We also show applications of anatomical labeling on a bronchoscopy guidance system. This paper performs automated labeling by using machine learning and combination optimization. The actual procedure consists of four steps: (a) extraction of tree structures of the bronchus regions extracted from CT images, (b) construction of AdaBoost classifiers, (c) computation of candidate names for all branches by using the classifiers, (d) selection of best combination of anatomical names. We applied the proposed method to 90 cases of 3D CT datasets. The experimental results showed that the proposed method can assign correct anatomical names to 86.9% of the bronchial branches up to the sub-segmental lobe branches. Also, we overlaid the anatomical names of bronchial branches on real bronchoscopic views to guide real bronchoscopy.