Multimodal Optical Imaging by Microendoscope

In the past decades, optical imaging field has been developing rapidly. Noninvasive imaging enabled by microendoscopes has become a promising tool for early cancer detection and imaging-guided surgery. In this chapter, we will mainly introduce most advances in the miniaturized microendoscope development, including photoacoustic, confocal fluorescence, multiphoton fluorescence, second-harmonic generation (SHG) label-free imaging, wide-field fluorescence, surface-enhanced Raman scattering (SERS) nanoparticle-based Raman spectroscopy. Enabled by the frontier micromachining techniques, micro-opto-electromechanical system (MOEMS)-based novel microendoscopes with various imaging modalities have been prototyped and further translated into clinics. The working principle of representative microendoscopes and optical imaging modalities will be introduced in detail

Robust analytic continuation of Green's functions via projection, pole estimation, and semidefinite relaxation

Green's functions of fermions are described by matrix-valued Herglotz-Nevanlinna functions. Since analytic continuation is fundamentally an ill-posed problem, the causal space described by the matrix-valued Herglotz-Nevanlinna structure can be instrumental in improving the accuracy and in enhancing the robustness with respect to noise. We demonstrate a three-pronged procedure for robust analytic continuation called PES: (1) Projection of data to the causal space. (2) Estimation of pole locations. (3) Semidefinite relaxation within the causal space. We compare the performance of PES with the recently developed Nevanlinna and Carath\'{e}odory continuation methods and find that PES is more robust in the presence of noise and does not require the usage of extended precision arithmetics. We also demonstrate that a causal projection improves the performance of the Nevanlinna and Carath\'{e}odory methods. The PES method is generalized to bosonic response functions, for which the Nevanlinna and Carath\'{e}odory continuation methods have not yet been developed. It is particularly useful for studying spectra with sharp features, as they occur in the study of molecules and band structures in solids.Comment: 14 pages, 5 figure

Genetic and clinical assessment of 2009 pandemic influenza in southern China

Introduction: South China has a proven role in the global epidemiology of previous influenza outbreaks due to its dual seasonal pattern. We present the virologic, genetic and clinical characterization of pandemic H1N1 influenza infection (pH1N1) in Shantou and Nanchang, cities in southern China, during the second wave of the 2009-2010 pandemic. Methodology: Nasopharyngeal swabs were collected from 165 individuals with influenza-like illness (ILI) who presented to the hospitals in Shantou and Nanchang. Laboratory diagnosis and characterization was performed by real-time PCR, virus isolation in embryonated chicken eggs, and sequencing. Results: pH1N1 activity was sustained in three different temporal patterns throughout the study period. The overall positivity rate of pH1N1 was 50% with major distribution among young adults between the ages of 13 and 30 years. High fever, cough, expectoration, chest pain, myalgia, nasal discharge and efficient viral replication were observed as major clinical markers whereas a substantial number of afebrile cases (17%) was also observed. Rate of hospitalization and disease severity (39%) and recovery (100%) were also high within the region. Furthermore, severe complications were likely to develop in young adults upon pH1N1 infection. Genetic characterization of the HA and NA genes of pH1N1 strains exhibited homogenous spread of pH1N1 strains with 99% identity with prototypic strains; however, minor unique mutations were also observed in the HA gene. Conclusion: The study illustrates the detailed characteristics of 2009 influenza pandemic in southern parts of China that might help to strategize preparedness for future pandemics and subsequent influenza seasons.</br

SurfCon: Synonym Discovery on Privacy-Aware Clinical Data

Unstructured clinical texts contain rich health-related information. To better utilize the knowledge buried in clinical texts, discovering synonyms for a medical query term has become an important task. Recent automatic synonym discovery methods leveraging raw text information have been developed. However, to preserve patient privacy and security, it is usually quite difficult to get access to large-scale raw clinical texts. In this paper, we study a new setting named synonym discovery on privacy-aware clinical data (i.e., medical terms extracted from the clinical texts and their aggregated co-occurrence counts, without raw clinical texts). To solve the problem, we propose a new framework SurfCon that leverages two important types of information in the privacy-aware clinical data, i.e., the surface form information, and the global context information for synonym discovery. In particular, the surface form module enables us to detect synonyms that look similar while the global context module plays a complementary role to discover synonyms that are semantically similar but in different surface forms, and both allow us to deal with the OOV query issue (i.e., when the query is not found in the given data). We conduct extensive experiments and case studies on publicly available privacy-aware clinical data, and show that SurfCon can outperform strong baseline methods by large margins under various settings.Comment: KDD 2019 (Accepted for Oral Presentation at the Research track

A new sparse representation framework for compressed sensing MRI

Abstract(#br)Compressed sensing based Magnetic Resonance imaging (MRI) via sparse representation (or transform) has recently attracted broad interest. The tight frame (TF)-based sparse representation is a promising approach in compressed sensing MRI. However, the conventional TF-based sparse representation is difficult to utilize the sparsity of the whole image. Since the whole image usually has different structure textures and a kind of tight frame can only represent a particular kind of ground object, how to reconstruct high-quality of magnetic resonance (MR) image is a challenge. In this work, we propose a new sparse representation framework, which fuses the double tight frame (DTF) into the mixed-norm regularization for MR image reconstruction from undersampled k -space data. In this framework, MR image is decomposed into smooth and nonsmooth regions. For the smooth regions, the wavelet TF-based weighted L 1 -norm regularization is developed to reconstruct piecewise-smooth information of image. For nonsmooth regions, we introduce the curvelet TF-based robust L 1 , a -norm regularization with the parameter to preserve the edge structural details and texture. To estimate the reasonable parameter, an adaptive parameter selection scheme is designed in robust L 1 , a -norm regularization. Experimental results demonstrate that the proposed method can achieve the best image reconstruction results when compared with other existing methods in terms of quantitative metrics and visual effect

LPS诱导的肺纤维细胞PTEN基因表达和Akt磷酸化蛋白表达的研究

Objective: To investigate PTEN gene expression and the Akt phosphorylation of protein expression in the LPS-induced lung fibroblast, to initially reveal the relation between PTEN gene and the Akt phosphorylated proteins to LPS-induced lung fibroblast proliferation mechanism. Methods: BrdU experiments was performed to evaluate the LPS-induced lung fibroblast proliferation,  RT-PCR and Western Blot analysis were used to analyze the PTEN gene expression and Western blot was performed to analyze Akt phosphorylated protein expression. Results: PTEN mRNA level of the experimental group were significantly lower than the control group (P&lt;0.05) with LPS simulation for 24h and 72h , and there were no significant difference between the experimental group and control group the experimental group and control group (P&gt;0.05) . PTEN protein expression levels of the experimental group were significantly lower than the control group (P&lt;0.05) , at 72h, and PTEN mRNA levels had no significant differences between these of the experimental and control group at 6h,12h and 24h(p&gt;0.05). Phosphorylation Akt protein level (relative to total Akt protein) was significantly higer than the control group (P&lt;0.05) at 24h and 72h, and phosphorylation Akt protein levels had no significant differences between these of the experimental and control group at 6h and 12h (P&gt;0.05) .Conclusion: PTEN gene and phosphorylation Akt protein involve in LPS-induced lung fibroblast proliferation signal transduction pathway.目的  探讨LPS诱导肺成纤维细胞PTEN基因表达和Akt磷酸化蛋白表达，初步揭示LPS诱导的肺成纤维细胞增殖机制中PTEN基因和Akt磷酸化蛋白的变化情况。方法  通过BrdU实验评价LPS诱导肺成纤维细胞增殖情况，通过RT-PCR和Western Blot分析LPS诱导LPS诱导肺成纤维细胞增殖后细胞内PTEN mRNA水平和蛋白表达情况，通过Western Blot分析LPS诱导肺成纤维细胞增殖后细胞Akt磷酸化蛋白表达情况。结果  在6h、12h时实验组和对照组PTEN mRNA转录水平差异无显著性（P&gt;0.05），24h和72h时实验组PTEN mRNA转录水平显著低于对照组（P&lt;0.05）。在6h、12h和24h时实验组和对照组PTEN mRNA转录水平差异无显著性（P&gt;0.05），在72h时实验组PTEN蛋白表达水平显著低于对照组（P&lt;0.05）。在6h、12h时实验组和对照组Akt磷酸化蛋白（相对总Akt蛋白）差异无显著性（P&gt;0.05），在24h和72h实验组Akt磷酸化蛋白（相对总Akt蛋白）显著低于对照组（P&lt;0.05）。结论  PTEN基因和Akt磷酸化蛋白参与了LPS诱导的肺成纤维细胞增殖信号转导途径