Novel water filtration of saline water in the outermost layer of mangrove roots

The scarcity of fresh water is a global challenge faced at present. Several desalination methods have been suggested to secure fresh water from sea water. However, conventional methods suffer from technical limitations, such as high power consumption, expensive operating costs, and limited system durability. In this study, we examined the feasibility of using halophytes as a novel technology of desalinating high-concentration saline water for long periods. This study investigated the biophysical characteristics of sea water filtration in the roots of the mangrove Rhizophora stylosa from a plant hydrodynamic point of view. R. stylosa can grow even in saline water, and the salt level in its roots is regulated within a certain threshold value through filtration. The root possesses a hierarchical, triple layered pore structure in the epidermis, and most Na+ ions are filtered at the first sublayer of the outermost layer. The high blockage of Na+ ions is attributed to the high surface zeta potential of the first layer. The second layer, which is composed of macroporous structures, also facilitates Na+ ion filtration. This study provides insights into the mechanism underlying water filtration through halophyte roots and serves as a basis for the development of a novel bio-inspired desalination method.Creative Research Initiative (Diagnosis of Biofluid Flow Phenomena and Biomimic Research) of the Ministry of Science, ICT and Future Planning (MSIP) , National Research Foundation (NRF) of Korea , ICT R&D program of MSIP/IITP (Korea

Automatic 3D Registration of Dental CBCT and Face Scan Data using 2D Projection images

This paper presents a fully automatic registration method of dental cone-beam computed tomography (CBCT) and face scan data. It can be used for a digital platform of 3D jaw-teeth-face models in a variety of applications, including 3D digital treatment planning and orthognathic surgery. Difficulties in accurately merging facial scans and CBCT images are due to the different image acquisition methods and limited area of correspondence between the two facial surfaces. In addition, it is difficult to use machine learning techniques because they use face-related 3D medical data with radiation exposure, which are difficult to obtain for training. The proposed method addresses these problems by reusing an existing machine-learning-based 2D landmark detection algorithm in an open-source library and developing a novel mathematical algorithm that identifies paired 3D landmarks from knowledge of the corresponding 2D landmarks. A main contribution of this study is that the proposed method does not require annotated training data of facial landmarks because it uses a pre-trained facial landmark detection algorithm that is known to be robust and generalized to various 2D face image models. Note that this reduces a 3D landmark detection problem to a 2D problem of identifying the corresponding landmarks on two 2D projection images generated from two different projection angles. Here, the 3D landmarks for registration were selected from the sub-surfaces with the least geometric change under the CBCT and face scan environments. For the final fine-tuning of the registration, the Iterative Closest Point method was applied, which utilizes geometrical information around the 3D landmarks. The experimental results show that the proposed method achieved an averaged surface distance error of 0.74 mm for three pairs of CBCT and face scan datasets.Comment: 8 pages, 6 figures, 2 table

Effects of Textural Properties on the Response of a SnO2-Based Gas Sensor for the Detection of Chemical Warfare Agents

The sensing behavior of SnO2-based thick film gas sensors in a flow system in the presence of a very low concentration (ppb level) of chemical agent simulants such as acetonitrile, dipropylene glycol methyl ether (DPGME), dimethyl methylphosphonate (DMMP), and dichloromethane (DCM) was investigated. Commercial SnO2 [SnO2(C)] and nano-SnO2 prepared by the precipitation method [SnO2(P)] were used to prepare the SnO2 sensor in this study. In the case of DCM and acetonitrile, the SnO2(P) sensor showed higher sensor response as compared with the SnO2(C) sensors. In the case of DMMP and DPGME, however, the SnO2(C) sensor showed higher responses than those of the SnO2(P) sensors. In particular, the response of the SnO2(P) sensor increased as the calcination temperature increased from 400 °C to 800 °C. These results can be explained by the fact that the response of the SnO2-based gas sensor depends on the textural properties of tin oxide and the molecular size of the chemical agent simulant in the detection of the simulant gases (0.1–0.5 ppm)

Nonspecific Interstitial Pneumonitis after Bortezomib and Thalidomide Treatment in a Multiple Myeloma Patient

Bortezomib, an inhibitor of 26S proteosome, is recently approved treatment option for multiple myeloma. Thalidomide, a drug with immunomodulating and antiangiogenic effects, has also shown promise as an effective treatment in multiple myeloma. Pulmonary complications are believed to be rare, especially interstitial lung disease. Here, we describe a patient with dyspnea and diffuse pulmonary infiltrates while receiving bortezomib and thalidomide in combination with dexamethasone for treatment-naïve multiple myeloma. Bronchoalveolar lavage demonstrated a significant decrease in the ratio of CD4 : CD8 T lymphocytes (CD4/8 ratio, 0.54). Extensive workup for other causes, including infections, was negative. A lung biopsy under video-assisted thorascopic surgery revealed a diagnosis of nonspecific interstitial pneumonitis. The symptoms and imaging study findings improved after initiating steroid treatment. Physicians should be aware of this potential complication in patients receiving the novel molecular-targeted antineoplastic agents, bortezomib and thalidomide, who present with dyspnea and new pulmonary infiltrates and fail to improve despite treatment with broad-spectrum antibiotics

Could Fractional Exhaled Nitric Oxide Test be Useful in Predicting Inhaled Corticosteroid Responsiveness in Chronic Cough? A Systematic Review

© 2016 Background Fractional exhaled nitric oxide (FENO) is a safe and convenient test for assessing T H 2 airway inflammation, which is potentially useful in the management of patients with chronic cough. Objective To summarize the current evidence on the diagnostic usefulness of FENO for predicting inhaled corticosteroid (ICS) responsiveness in patients with chronic cough. Methods A systematic literature review was conducted to identify articles published in peer-reviewed journals up to February 2015, without language restriction. We included studies that reported the usefulness of FENO (index test) for predicting ICS responsiveness (reference standard) in patients with chronic cough (target condition). The data were extracted to construct a 2 × 2 accuracy table. Study quality was assessed with Quality Assessment of Diagnostic Accuracy Studies 2. Results We identified 5 original studies (2 prospective and 3 retrospective studies). We identified considerable heterogeneities in study design and outcome definitions, and thus were unable to perform a meta-analysis. The proportion of ICS responders ranged from 44% to 59%. Sensitivity and specificity ranged from 53% to 90%, and from 63% to 97%, respectively. The reported area under the curve ranged from abou t 0.60 to 0.87; however, studies with a prospective design and a lower prevalence of asthma had lower area under the curve values. None measured placebo effects or objective cough frequency. Conclusions We did not find strong evidence to support the use of FENO tests for predicting ICS responsiveness in chronic cough. Further studies need to have a randomized, placebo-controlled design, and should use validated measurement tools for cough. Standardization would facilitate the development of clinical evidence