HOLLOW GOLD NANOSTRUCTURES PREPARED BY GALVANIC REPLACEMENT REACTION: SYNTHESIS AND OPTICAL PROPERTIES

This work describes a facile synthesis of hollow Au nanostructures involved in the galvanic replacement reaction utilising Ag nanoparticles as the templates. The effect of reaction conditions, including PVP concentration and reaction time on the morphology of Ag templates was investigated. Using Ag nanocubic-shape templates, 50 nm hollow Au nanostructures were prepared. The result indicated that the wavelength of SPR peak of the hollow Au nanostructures was strongly affected by Au precursor content and could be tuned between 460 and 860 nm when altering the volume of the Au precursor solution from 0.5 to 3 ml. The ability of conversion of photo energy into heat of the hollow Au nanostructures was also exploited. The optical heating data of Au solution (165 µg/ml) with an 808 nm laser at a power of 1.8 W showed that the sample temperature reached to 55 oC after just 5 min irradiation. The successfulness in fabrication hollow Au nanostructures having SPR peak in NIR region, relative small size and high capacity of conversion of photo energy into heat make them become a novel and promising material for photo thermal and photo imaging applications

Anisotropy, Phonon Modes, and Free Charge Carrier Parameters in Monoclinic β-Gallium Oxide Single Crystals

We derive a dielectric function tensor model approach to render the optical response of monoclinic and triclinic symmetry materials with multiple uncoupled infrared and far-infrared active modes. We apply our model approach to monoclinic β-Ga2O3 single-crystal samples. Surfaces cut under different angles from a bulk crystal, (010) and (2̅01), are investigated by generalized spectroscopic ellipsometry within infrared and far-infrared spectral regions. We determine the frequency dependence of 4 independent β-Ga2O3 Cartesian dielectric function tensor elements by matching large sets of experimental data using a point-by-point data inversion approach. From matching our monoclinic model to the obtained 4 dielectric function tensor components, we determine all infrared and far-infrared active transverse optic phonon modes with Au and Bu symmetry, and their eigenvectors within the monoclinic lattice. We find excellent agreement between our model results and results of density functional theory calculations. We derive and discuss the frequencies of longitudinal optical phonons in β-Ga2O3. We derive and report density and anisotropic mobility parameters of the free charge carriers within the tin-doped crystals. We discuss the occurrence of longitudinal phonon plasmon coupled modes in β-Ga2O3 and provide their frequencies and eigenvectors. We also discuss and present monoclinic dielectric constants for static electric fields and frequencies above the reststrahlen range, and we provide a generalization of the Lyddane-Sachs-Teller relation for monoclinic lattices with infrared and far-infrared active modes.We find that the generalized Lyddane-Sachs-Teller relation is fulfilled excellently for β-Ga2O3

Broadening horizons: the case for capturing function and the role of health informatics in its use

Background Human activity and the interaction between health conditions and activity is a critical part of understanding the overall function of individuals. The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) models function as all aspects of an individual’s interaction with the world, including organismal concepts such as individual body structures, functions, and pathologies, as well as the outcomes of the individual’s interaction with their environment, referred to as activity and participation. Function, particularly activity and participation outcomes, is an important indicator of health at both the level of an individual and the population level, as it is highly correlated with quality of life and a critical component of identifying resource needs. Since it reflects the cumulative impact of health conditions on individuals and is not disease specific, its use as a health indicator helps to address major barriers to holistic, patient-centered care that result from multiple, and often competing, disease specific interventions. While the need for better information on function has been widely endorsed, this has not translated into its routine incorporation into modern health systems. Purpose We present the importance of capturing information on activity as a core component of modern health systems and identify specific steps and analytic methods that can be used to make it more available to utilize in improving patient care. We identify challenges in the use of activity and participation information, such as a lack of consistent documentation and diversity of data specificity and representation across providers, health systems, and national surveys. We describe how activity and participation information can be more effectively captured, and how health informatics methodologies, including natural language processing (NLP), can enable automatically locating, extracting, and organizing this information on a large scale, supporting standardization and utilization with minimal additional provider burden. We examine the analytic requirements and potential challenges of capturing this information with informatics, and describe how data-driven techniques can combine with common standards and documentation practices to make activity and participation information standardized and accessible for improving patient care. Recommendations We recommend four specific actions to improve the capture and analysis of activity and participation information throughout the continuum of care: (1) make activity and participation annotation standards and datasets available to the broader research community; (2) define common research problems in automatically processing activity and participation information; (3) develop robust, machine-readable ontologies for function that describe the components of activity and participation information and their relationships; and (4) establish standards for how and when to document activity and participation status during clinical encounters. We further provide specific short-term goals to make significant progress in each of these areas within a reasonable time frame

A comprehensive study of mobility functioning information in clinical notes: Entity hierarchy, corpus annotation, and sequence labeling

Background Secondary use of Electronic Health Records (EHRs) has mostly focused on health conditions (diseases and drugs). Function is an important health indicator in addition to morbidity and mortality. Nevertheless, function has been overlooked in accessing patients’ health status. The World Health Organization (WHO)’s International Classification of Functioning, Disability and Health (ICF) is considered the international standard for describing and coding function and health states. We pioneer the first comprehensive analysis and identification of functioning concepts in the Mobility domain of the ICF. Results Using physical therapy notes at the National Institutes of Health’s Clinical Center, we induced a hierarchical order of mobility-related entities including 5 entities types, 3 relations, 8 attributes, and 33 attribute values. Two domain experts manually curated a gold standard corpus of 14,281 nested entity mentions from 400 clinical notes. Inter-annotator agreement (IAA) of exact matching averaged 92.3 % F1-score on mention text spans, and 96.6 % Cohen’s kappa on attributes assignments. A high-performance Ensemble machine learning model for named entity recognition (NER) was trained and evaluated using the gold standard corpus. Average F1-score on exact entity matching of our Ensemble method (84.90 %) outperformed popular NER methods: Conditional Random Field (80.4 %), Recurrent Neural Network (81.82 %), and Bidirectional Encoder Representations from Transformers (82.33 %). Conclusions The results of this study show that mobility functioning information can be reliably captured from clinical notes once adequate resources are provided for sequence labeling methods. We expect that functioning concepts in other domains of the ICF can be identified in similar fashion

Identification of Immunogenic Salmonella enterica Serotype Typhi Antigens Expressed in Chronic Biliary Carriers of S. Typhi in Kathmandu, Nepal

Background: Salmonella enterica serotype Typhi can colonize and persist in the biliary tract of infected individuals, resulting in a state of asymptomatic chronic carriage. Chronic carriers may act as persistent reservoirs of infection within a community and may introduce infection to susceptible individuals and new communities. Little is known about the interaction between the host and pathogen in the biliary tract of chronic carriers, and there is currently no reliable diagnostic assay to identify asymptomatic S. Typhi carriage. Methodology/Principal Findings To study host-pathogen interactions in the biliary tract during S. Typhi carriage, we applied an immunoscreening technique called in vivo-induced antigen technology (IVIAT), to identify potential biomarkers unique to carriers. IVIAT identifies humorally immunogenic bacterial antigens expressed uniquely in the in vivo environment, and we hypothesized that S. Typhi surviving in the biliary tract of humans may express a distinct antigenic profile. Thirteen S. Typhi antigens that were immunoreactive in carriers, but not in healthy individuals from a typhoid endemic area, were identified. The identified antigens included a number of putative membrane proteins, lipoproteins, and hemolysin-related proteins. YncE (STY1479), an uncharacterized protein with an ATP-binding motif, gave prominent responses in our screen. The response to YncE in patients whose biliary tract contained S. Typhi was compared to responses in patients whose biliary tract did not contain S. Typhi, patients with acute typhoid fever, and healthy controls residing in a typhoid endemic area. Seven of 10 (70%) chronic carriers, 0 of 8 bile culture-negative controls (0%), 0 of 8 healthy Bangladeshis (0%), and 1 of 8 (12.5%) Bangladeshis with acute typhoid fever had detectable anti-YncE IgG in blood. IgA responses were also present. Conclusions/Significance: Further evaluation of YncE and other antigens identified by IVIAT could lead to the development of improved diagnostic assays to identify asymptomatic S. Typhi carriers

Inductive identification of functional status information and establishing a gold standard corpus: a case study on the mobility domain

The importance of functional status information (FSI) has become increasingly evident in recent years [1, 2]. However, implementation, application, and normalization of FSI in health care and Electronic Health Records (EHRs) have been largely underexplored. The World Health Organization's International Classification of Functioning, Disability and Health (ICF) [3] is considered to be the international standard for describing and coding function and health states. Nevertheless, the ICF provides only a limited vocabulary for recognizing FSI descriptions, since its purpose is to organize concepts related to functioning rather than to provide a comprehensive terminology or a complete set of relations between concepts. While the free text portion of EHRs might provide a more complete picture of health status, treatment, and progress, current Natural Language Processing (NLP) methods largely focus on extracting medical conditions (e.g. diagnoses and symptoms, etc.). The absence of a standardized functional terminology and incompleteness of the ICF as a vocabulary source makes it challenging to build a NLP system to extract FSI from EHR free text. Our work takes the first step towards extraction of FSI from free text by systematically identifying the structure of FSI related to Mobility, a key domain of the ICF and an important domain in the determination of work disability. Our interdisciplinary research group inductively evaluated examples extracted from over 1,200 Physical Therapy (PT) notes from the Clinical Center of the National Institutes of Health (NIH). This extensive work resulted in a nested entity structure comprised of 2 entities, 3 sub-entities, 8 attributes, and 21 attribute values. Furthermore, we have manually curated the first gold standard corpus of 200 double-annotated and 50 triple-annotated PT notes. Our inter-annotator agreement (IAA) averages 97% F1-score on partial textual span matching and from 0.4 to 0.9 Siegel & Castellan's kappa on attribute value matching. Such a rich semantic corpus of Mobility FSI is valuable and a promising resource for future statistical learning. Our method is also adaptable to other domains of the ICF