Molecular Sensors for Anions - A Computational Study

Ph.DDOCTOR OF PHILOSOPH

Analysis of Differential Gel Electrophoresis of Paclitaxol Resistant and Sensitive Lung Adenocarcinoma Cells' Secretome

Background and objective Paclitaxol (PTX) resistance is one of main factors which affect the outcome of chemotherapy of lung adenocarcinoma. The aim of this study is to compare the secreted protein expression profiles between Paclitaxol (PTX) resistant and sensitive lung adenocarcinoma cells by proteomic research method, so as to provide evidence of choosing individual chemotherapy drugs in clinical treatment. Methods Total secreted proteins extracted from a PTX sensitive cell line A549 and a PTX resistant cell line A549-Taxol were separated by fluorscent differential gel electrophoresis (DIGE). High quality 2-DE profiles were obtained and analyzed by Decyder 6.5 analysis software to screen differentially expressed protein spots. Those spots were identified by mass spectrometry. Results 2-DE patterns of lung adenocarcinoma cells with high-resolution and reproducibility were obtained. 76 significantly differentially expressed protein spots were screened, 19 proteins were identified by mass spectrometry. The identified proteins could be classified into different catogories: metabolic enzyme, extracellular matrix (ECM) degradation enzyme, cytokine, signal transducer, cell adhesion, and so on. Conclusion Multiple secreted proteins related to chemoresistance of A549-Taxol cells were identified in this study for the first time. The results presented here would provide clues to identify new serologic chemoresistant biomarkers of NSCLC

Unsupervised discovery of multilevel statistical video structures using hierarchical hidden Markov models

Structure elements in a time sequence (e.g. video) are repetitive segments with consistent deterministic or stochastic characteristics. While most existing work in detecting structures follow a supervised paradigm, we propose a fully unsupervised statistical solution in this paper. We present a unified approach to structure discovery from long video sequences as simultaneously finding the statistical descriptions of structure and locating segments that matches the descriptions. We model the multilevel statistical structure as hierarchical hidden Markov models, and present efficient algorithms for learning both the parameters and the model structure. When tested on a specific domain, soccer video, the unsupervised learning scheme achieves very promising results: it automatically discovers the statistical descriptions of high-level structures, and at the same time achieves even slightly better accuracy in detecting discovered structures in unlabelled videos than a supervised approach designed with domain knowledge and trained with comparable hidden Markov models

Quality of Life of Adults with Chronic Spinal Cord Injury in Mainland China: A Cross-Sectional Study

Objective: To evaluate the quality of life of patients with chronic spinal cord injury in mainland China. Design: Cross-sectional study. Subjects: A total of 247 adults ≥ 1 year post-SCI in mainland China. Methods: The World Health Organization (WHO) Quality of Life Scale Brief Version (WHOQOL-BREF) and the add-on modules on disability-related QoL (WHOQOL-DIS) were used to assess quality of life. Anxiety/depression was measured using the Zung Self-Rating Anxiety/Depression Scale. Quality of life was compared with that of reference populations from China, Korea, the international field trial (23 countries). Multivariate linear regression was conducted to determine the factors that might be associated with quality of life. Results: The means of the 4 domains of the WHOQOLBREF varied from 11.5 to 13.0. The mean of the 12- item WHOQOL-DIS module was 38.7. The quality of life of the participants as measured by the WHOQOLBREF was 1.1--4.7 points lower than that of the global reference population, while quality of life as measured by the WHOQOL-DIS module was 1.2 points lower than that of the Korean data. Anxiety and depression were negative factors associated with quality of life (p \u3c 0.05). Better community integration was a positive factor for physical quality of life and quality of life as measured by the WHOQOL-DIS module (p \u3c0.01). Conclusion: The quality of life of adults with chronic spinal cord injury in mainland China was lower compared with reference populations. Duration of spinal cord injury, sex, community integration, anxiety, and depression were related to quality of life

Phylogenetic analysis of porcine parvoviruses from swine samples in China

<p>Abstract</p> <p>Background</p> <p>Porcine parvovirus (PPV) usually causes reproductive failure in sows. The objective of the present study was to analyze the phylogenetic distribution and perform molecular characterization of PPVs isolated in China, as well as to identify two field strains, LZ and JY. The data used in this study contained the available sequences for NS1 and VP2 from GenBank, as well as the two aforementioned Chinese strains.</p> <p>Results</p> <p>Phylogenetic analysis shows that the PPV sequences are divided into four groups. The early Chinese PPV isolates are Group I viruses, and nearly all of the later Chinese PPV isolates are Group II viruses. LZ belongs to group II, whereas the JY strain is a Group III virus. This is the first report on the isolation of a Group III virus in China. The detection of selective pressures on the PPV genome shows that the NS1 and VP2 genes are under purifying selection and positive selection, respectively. Moreover, the amino acids in the VP2 capsid are highly variable because of the positive selection.</p> <p>Conclusions</p> <p>Our study provides new molecular data on PPV strains in China, and emphasizes the importance of etiological studies of PPV in pigs.</p

In-vitro and in-vivo phenotype of type Asia 1 foot-and-mouth disease viruses utilizing two non-RGD receptor recognition sites

<p>Abstract</p> <p>Background</p> <p>Foot-and-mouth disease virus (FMDV) uses a highly conserved Arg-Gly-Asp (RGD) triplet for attachment to host cells and this motif is believed to be essential for virus viability. Previous sequence analyses of the 1D-encoding region of an FMDV field isolate (Asia1/JS/CHA/05) and its two derivatives indicated that two viruses, which contained an Arg-Asp-Asp (RDD) or an Arg-Ser-Asp (RSD) triplet instead of the RGD integrin recognition motif, were generated serendipitously upon short-term evolution of field isolate in different biological environments. To examine the influence of single amino acid substitutions in the receptor binding site of the RDD-containing FMD viral genome on virus viability and the ability of non-RGD FMDVs to cause disease in susceptible animals, we constructed an RDD-containing FMDV full-length cDNA clone and derived mutant molecules with RGD or RSD receptor recognition motifs. Following transfection of BSR cells with the full-length genome plasmids, the genetically engineered viruses were examined for their infectious potential in cell culture and susceptible animals.</p> <p>Results</p> <p>Amino acid sequence analysis of the 1D-coding region of different derivatives derived from the Asia1/JS/CHA/05 field isolate revealed that the RDD mutants became dominant or achieved population equilibrium with coexistence of the RGD and RSD subpopulations at an early phase of type Asia1 FMDV quasispecies evolution. Furthermore, the RDD and RSD sequences remained genetically stable for at least 20 passages. Using reverse genetics, the RDD-, RSD-, and RGD-containing FMD viruses were rescued from full-length cDNA clones, and single amino acid substitution in RDD-containing FMD viral genome did not affect virus viability. The genetically engineered viruses replicated stably in BHK-21 cells and had similar growth properties to the parental virus. The RDD parental virus and two non-RGD recombinant viruses were virulent to pigs and bovines that developed typical clinical disease and viremia.</p> <p>Conclusions</p> <p>FMDV quasispecies evolving in a different biological environment gained the capability of selecting different receptor recognition site. The RDD-containing FMD viral genome can accommodate substitutions in the receptor binding site without additional changes in the capsid. The viruses expressing non-RGD receptor binding sites can replicate stably in vitro and produce typical FMD clinical disease in susceptible animals.</p

Insights into the Jahn-Teller effect in layered oxide cathode materials for potassium-ion batteries

Potassium-ion batteries (PIBs) have attracted increasing interest as promising alternatives to lithium-ion batteries (LIBs) in large-scale electrical energy storage systems due to the potential price advantages, abundant availability of potassium resources, and low standard redox potential of potassium. However, the pursuit of suitable cathode materials that exhibit desirable characteristics such as voltage platforms, high capacity, and long cycling stability is of utmost importance. Recently, layered transition-metal oxides for PIBs offer great potential due to their high theoretical capacity, suitable voltage range, and eco-friendliness. Nevertheless, the progress of KxMO2 cathodes in PIBs faces obstacles due to the detrimental effects of structural disorder and irreversible phase transitions caused by the Jahn-Teller effect. This review provides a brief description of the origin and mechanism of the Jahn-Teller effect, accompanied by the proposed principles to mitigate this phenomenon. In particular, the current status of KxMO2 cathodes for PIBs, is summarized highlighting the challenges posed by the Jahn-Teller effect. Furthermore, promising strategies, such as composition modulation, synthesis approaches, and surface modification, are proposed to alleviate and suppress the Jahn-Teller effect. These strategies offer valuable insights into the prospects of innovative cathode materials and provide a foundation for future research in the field of PIBs

Fundamentally manipulating the electronic structure of polar bifunctional catalysts for lithium-sulfur batteries: Heterojunction design versus doping engineering

Heterogeneous structures and doping strategies have been intensively used to manipulate the catalytic conversion of polysulfides to enhance reaction kinetics and suppress the shuttle effect in lithium-sulfur (Li-S) batteries. However, understanding how to select suitable strategies for engineering the electronic structure of polar catalysts is lacking. Here, a comparative investigation between heterogeneous structures and doping strategies is conducted to assess their impact on the modulation of the electronic structures and their effectiveness in catalyzing the conversion of polysulfides. These findings reveal that Co0.125Zn0.875Se, with metal-cation dopants, exhibits superior performance compared to CoSe2/ZnSe heterogeneous structures. The incorporation of low Co2+ dopants induces the subtle lattice strain in Co0.125Zn0.875Se, resulting in the increased exposure of active sites. As a result, Co0.125Zn0.875Se demonstrates enhanced electron accumulation on surface Se sites, improved charge carrier mobility, and optimized both p-band and d-band centers. The Li-S cells employing Co0.125Zn0.875Se catalyst demonstrate significantly improved capacity (1261.3 mAh g−1 at 0.5 C) and cycle stability (0.048% capacity delay rate within 1000 cycles at 2 C). This study provides valuable guidance for the modulation of the electronic structure of typical polar catalysts, serving as a design directive to tailor the catalytic activity of advanced Li-S catalysts

Deep learning-based image segmentation model using an MRI-based convolutional neural network for physiological evaluation of the heart

Background and Objective: Cardiovascular disease is a high-fatality health issue. Accurate measurement of cardiovascular function depends on precise segmentation of physiological structure and accurate evaluation of functional parameters. Structural segmentation of heart images and calculation of the volume of different ventricular activity cycles form the basis for quantitative analysis of physiological function and can provide the necessary support for clinical physiological diagnosis, as well as the analysis of various cardiac diseases. Therefore, it is important to develop an efficient heart segmentation algorithm.Methods: A total of 275 nuclear magnetic resonance imaging (MRI) heart scans were collected, analyzed, and preprocessed from Huaqiao University Affiliated Strait Hospital, and the data were used in our improved deep learning model, which was designed based on the U-net network. The training set included 80% of the images, and the remaining 20% was the test set. Based on five time phases from end-diastole (ED) to end-systole (ES), the segmentation findings showed that it is possible to achieve improved segmentation accuracy and computational complexity by segmenting the left ventricle (LV), right ventricle (RV), and myocardium (myo).Results: We improved the Dice index of the LV to 0.965 and 0.921, and the Hausdorff index decreased to 5.4 and 6.9 in the ED and ES phases, respectively; RV Dice increased to 0.938 and 0.860, and the Hausdorff index decreased to 11.7 and 12.6 in the ED and ES, respectively; myo Dice increased to 0.889 and 0.901, and the Hausdorff index decreased to 8.3 and 9.2 in the ED and ES, respectively.Conclusion: The model obtained in the final experiment provided more accurate segmentation of the left and right ventricles, as well as the myocardium, from cardiac MRI. The data from this model facilitate the prediction of cardiovascular disease in real-time, thereby providing potential clinical utility