Learning semi-supervised enrichment of longitudinal imaging-genetic data for improved prediction of cognitive decline.

BACKGROUND: Alzheimer's Disease (AD) is a progressive memory disorder that causes irreversible cognitive decline. Given that there is currently no cure, it is critical to detect AD in its early stage during the disease progression. Recently, many statistical learning methods have been presented to identify cognitive decline with temporal data, but few of these methods integrate heterogeneous phenotype and genetic information together to improve the accuracy of prediction. In addition, many of these models are often unable to handle incomplete temporal data; this often manifests itself in the removal of records to ensure consistency in the number of records across participants. RESULTS: To address these issues, in this work we propose a novel approach to integrate the genetic data and the longitudinal phenotype data to learn a fixed-length "enriched" biomarker representation derived from the temporal heterogeneous neuroimaging records. Armed with this enriched representation, as a fixed-length vector per participant, conventional machine learning models can be used to predict clinical outcomes associated with AD. CONCLUSION: The proposed method shows improved prediction performance when applied to data derived from Alzheimer's Disease Neruoimaging Initiative cohort. In addition, our approach can be easily interpreted to allow for the identification and validation of biomarkers associated with cognitive decline.

Scaling multi-instance support vector machine to breast cancer detection on the BreaKHis dataset.

MOTIVATION: Breast cancer is a type of cancer that develops in breast tissues, and, after skin cancer, it is the most commonly diagnosed cancer in women in the United States. Given that an early diagnosis is imperative to prevent breast cancer progression, many machine learning models have been developed in recent years to automate the histopathological classification of the different types of carcinomas. However, many of them are not scalable to large-scale datasets. RESULTS: In this study, we propose the novel Primal-Dual Multi-Instance Support Vector Machine to determine which tissue segments in an image exhibit an indication of an abnormality. We derive an efficient optimization algorithm for the proposed objective by bypassing the quadratic programming and least-squares problems, which are commonly employed to optimize Support Vector Machine models. The proposed method is computationally efficient, thereby it is scalable to large-scale datasets. We applied our method to the public BreaKHis dataset and achieved promising prediction performance and scalability for histopathological classification. AVAILABILITY AND IMPLEMENTATION: Software is publicly available at: https://1drv.ms/u/s!AiFpD21bgf2wgRLbQq08ixD0SgRD?e=OpqEmY. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Recent progress in photoactive organic field-effect transistors.

Recent progress in photoactive organic field-effect transistors (OFETs) is reviewed. Photoactive OFETs are divided into light-emitting (LE) and light-receiving (LR) OFETs. In the first part, LE-OFETs are reviewed from the viewpoint of the evolution of device structures. Device performances have improved in the last decade with the evolution of device structures from single-layer unipolar to multi-layer ambipolar transistors. In the second part, various kinds of LR-OFETs are featured. These are categorized according to their functionalities: phototransistors, non-volatile optical memories, and photochromism-based transistors. For both, various device configurations are introduced: thin-film based transistors for practical applications, single-crystalline transistors to investigate fundamental physics, nanowires, multi-layers, and vertical transistors based on new concepts.

Efficient adhesion-based plasma membrane isolation for cell surface N-glycan analysis.

Glycans, which decorate cell surfaces, play crucial roles in various physiological events involving cell surface recognition. Despite the importance of surface glycans, most analyses have been performed using total cells or whole membranes rather than plasma membranes due to difficulties related to isolation. In the present study, we employed an adhesion-based method for plasma membrane isolation to analyze N-glycans on cell surfaces. Cells were attached to polylysine-coated glass plates and then ruptured by hypotonic pressure. After washing to remove intracellular organelles, only a plasma membrane fraction remained attached to the plates, as confirmed by fluorescence imaging using organelle-specific probes. The plate was directly treated with trypsin to digest and detach the glycoproteins from the plasma membrane. From the resulting glycopeptides, N-glycans were released and analyzed using MALDI-TOF mass spectrometry and HPLC. When N-glycan profiles obtained by this method were compared to those by other methods, the amount of high-mannose type glycans mainly contaminated from the endoplasmic reticulum was dramatically reduced, which enabled the efficient detection of complex type glycans present on the cell surface. Moreover, this method was successfully used to analyze the increase of high-mannose glycans on the surface as induced by a mannosidase inhibitor treatment.

Early outcomes of video-assisted thoracic surgery (VATS) Ivor Lewis operation for esophageal squamous cell carcinoma: the extracorporeal anastomosis technique.

PURPOSE: Although the use of a minimally invasive approach in esophageal cancer surgery is gradually increasing, it is generally performed using cervical anastomosis because of the difficulty of intrathoracic anastomosis. Here, we describe our technique for performing intrathoracic esophagogastrostomy using a typical video-assisted thoracic surgery (VATS) approach. METHODS: Between September 2009 and July 2011, VATS esophagectomy and intrathoracic anastomosis was performed in 31 esophageal cancer patients with a utility incision made by a segmental rib resection to enhance the extracorporeal insertion of the end-to-end stapler. We retrospectively reviewed the clinical records of these patients. RESULTS: There were no intraoperative events related to the VATS procedure. The mean VATS time was 180.2 ± 39.2 min. The mean postoperative hospital stay was 15.2 days (range, 11 to 38 d). No significant pulmonary complications were observed. Five patients developed vocal cord palsy due to radical mediastinal lymphadenectomy. No anastomotic complications such as leaking or stricture were observed. Only 1 patient had postoperative pain requiring analgesics. CONCLUSIONS: Our technique can be safely and effectively performed for intrathoracic anastomosis in esophageal surgery with favorable early outcomes and reduced postoperative pulmonary complications.

Studies of tetracene- and pentacene-based organic thin-film transistors fabricated by the neutral cluster beam deposition method.

The neutral cluster beam deposition (NCBD) method has been applied to produce and characterize organic thin-film transistors (OTFTs) based upon tetracene and pentacene molecules as active layers. Organic thin films were prepared by the NCBD method on hexamethyldisilazane (HMDS)-untreated and -pretreated silicon dioxide (SiO2) substrates at room temperature. The surface morphology and structures for the tetracene and pentacene thin films were examined by atomic force microscopy (AFM) and X-ray diffraction (XRD). The measurements demonstrate that the weakly bound and highly directional neutral cluster beams are efficient in producing high-quality single-crystalline thin films with uniform, smooth surfaces and that SiO2 surface treatment with HMDS enhances the crystallinity of the pentacene thin-film phase. Tetracene- and pentacene-based OTFTs with the top-contact structure showed typical source-drain current modulation behavior with different gate voltages. Device parameters such as hole carrier mobility, current on/off ratio, threshold voltage, and subthreshold slope have been derived from the current-voltage characteristics together with the effects of surface treatment with HMDS. In particular, the high field-effect room-temperature mobilities for the HMDS-untreated OTFTs are found to be comparable to the most widely reported values for the respective untreated tetracene and pentacene thin-film transistors. The device performance strongly correlates with the surface morphology, and the structural properties of the organic thin films are discussed.

Isolation of Fusobacterium nucleatum from subgingival plaque in Korean / 대한치주과학회지

The purpose of this study was to isolate and characterize the Fusobacterium nucleatum (F. nucleatum) from subgingival plaque in Korean periodontitis patients. The subgingival plaque samples of periodontitis patient were collected with sterilized paper point. The paper point was put into reduced transfer medium and then immediately transferred to laboratory. The subgingival samples were diluted by 10,000 folds and plated on F. nucleatum-selective media agar plate. The plates were incubated at 37degrees C in an anaerobic chamber for 3 days. The violet-colored colonies were selected and subjected to further verification whether those are F. nucleatum or not. For further confirmation, 16S rRNA genes (rDNA) were cloned from each of bacterial clones and determined sequence of 16S rDNA. In this study, we found 17 distinct clinical isolates of F. nucleatum from subgingival plaque. The clinical isolates will be a useful in various studies in periodontology.