Modeling the Combined Effects of River Stage and Groundwater Flow on Riverbank Stability Before and After Dam Removal

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Land Subsidence Caused by Groundwater Exploitation in Yunlin, Taiwan

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Toll-like receptor 9 agonist enhances anti-tumor immunity and inhibits tumor-associated immunosuppressive cells numbers in a mouse cervical cancer model following recombinant lipoprotein therapy

BACKGROUND: Although cytotoxic T lymphocytes (CTLs) play a major role in eradicating cancer cells during immunotherapy, the cancer-associated immunosuppressive microenvironment often limits the success of such therapies. Therefore, the simultaneous induction of cancer-specific CTLs and reversal of the immunosuppressive tumor microenvironment may be more effectively achieved through a single therapeutic vaccine. A recombinant lipoprotein with intrinsic Toll-like receptor 2 (TLR2) agonist activity containing a mutant form of E7 (E7m) and a bacterial lipid moiety (rlipo-E7m) has been demonstrated to induce robust CTL responses against small tumors. This treatment in combination with other TLR agonists is able to eliminate large tumors. METHODS: Mouse bone marrow-derived dendritic cells (DCs) were employed to determine the synergistic production of pro-inflammatory cytokines upon combination of rlipo-E7m and other TLR agonists. Antigen-specific CTL responses were investigated using immunospots or in vivo cytolytic assays after immunization in mice. Mice bearing various tumor sizes were used to evaluate the anti-tumor effects of the formulation. Specific subpopulations of immunosuppressive cells in the tumor infiltrate were quantitatively determined by flow cytometry. RESULTS: We demonstrate that a TLR9 agonist (unmethylated CpG oligodeoxynucleotide, CpG ODN) enhances CTL responses and eradicates large tumors when combined with rlipo-E7m. Moreover, combined treatment with rlipo-E7m and CpG ODN effectively increases tumor infiltration by CTLs and reduces the numbers of myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs) and regulatory T cells (Tregs) in the tumor microenvironment. CONCLUSION: These findings suggest that the dramatic anti-tumor effects of the recombinant lipoprotein together with CpG ODN may reflect the amplification of CTL responses and the repression of the immunosuppressive environment. This promising approach could be applied for the development of additional therapeutic cancer vaccines

Diagnosis of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning

Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks. Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation of PCV. Results: AG-CNN is validated with a dataset containing 167 FA sequences of PCV and 70 FA sequences of CNV. AG-CNN achieves a classification accuracy of 82.80% at image level, and 86.21% at patient-level for PCV. Grad-CAM shows that regions contributing to decision-making have on average 21.91% agreement with pathological regions identified by experts. AG-PCVNet is validatedwith56PCV sequences from the EVEREST-I study and achieves a balanced accuracy of 81.132% and dice score of 0.54. Conclusions: The developed software provides a means of performing detection and segmentation of PCV on FA images for the first time. This study is a promising step in changing the diagnostic procedure of PCV and therefore improving the detection rate of PCV using FA alone. Translational Relevance: The developed deep learning system enables early diagnosis of PCV using FA to assist the physician in choosing the best treatment for optimal visual prognosis. Introductio

Diagnosis of Polypoidal Choroidal Vasculopathy from Fluorescein Angiography Using Deep Learning

Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks. Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation of PCV. Results: AG-CNN is validated with a dataset containing 167 FA sequences of PCV and 70 FA sequences of CNV. AG-CNN achieves a classification accuracy of 82.80% at image-level, and 86.21% at patient-level for PCV. Grad-CAM shows that regions contributing to decision-making have on average 21.91% agreement with pathological regions identified by experts. AG-PCVNet is validated with 56 PCV sequences from the EVEREST-I study and achieves a balanced accuracy of 81.132% and dice score of 0.54. Conclusions: The developed software provides a means of performing detection and segmentation of PCV on FA images for the first time. This study is a promising step in changing the diagnostic procedure of PCV and therefore improving the detection rate of PCV using FA alone. Translational Relevance: The developed deep learning system enables early diagnosis of PCV using FA to assist the physician in choosing the best treatment for optimal visual prognosis

Ventricular divergence correlates with epicardial wavebreaks and predicts ventricular arrhythmia in isolated rabbit hearts during therapeutic hypothermia

INTRODUCTION: High beat-to-beat morphological variation (divergence) on the ventricular electrogram during programmed ventricular stimulation (PVS) is associated with increased risk of ventricular fibrillation (VF), with unclear mechanisms. We hypothesized that ventricular divergence is associated with epicardial wavebreaks during PVS, and that it predicts VF occurrence. METHOD AND RESULTS: Langendorff-perfused rabbit hearts (n = 10) underwent 30-min therapeutic hypothermia (TH, 30°C), followed by a 20-min treatment with rotigaptide (300 nM), a gap junction modifier. VF inducibility was tested using burst ventricular pacing at the shortest pacing cycle length achieving 1:1 ventricular capture. Pseudo-ECG (p-ECG) and epicardial activation maps were simultaneously recorded for divergence and wavebreaks analysis, respectively. A total of 112 optical and p-ECG recordings (62 at TH, 50 at TH treated with rotigaptide) were analyzed. Adding rotigaptide reduced ventricular divergence, from 0.13±0.10 at TH to 0.09±0.07 (p = 0.018). Similarly, rotigaptide reduced the number of epicardial wavebreaks, from 0.59±0.73 at TH to 0.30±0.49 (p = 0.036). VF inducibility decreased, from 48±31% at TH to 22±32% after rotigaptide infusion (p = 0.032). Linear regression models showed that ventricular divergence correlated with epicardial wavebreaks during TH (p<0.001). CONCLUSION: Ventricular divergence correlated with, and might be predictive of epicardial wavebreaks during PVS at TH. Rotigaptide decreased both the ventricular divergence and epicardial wavebreaks, and reduced the probability of pacing-induced VF during TH

Genetic copy number variants in myocardial infarction patients with hyperlipidemia

<p>Abstract</p> <p>Background</p> <p>Cardiovascular disease is the chief cause of death in Taiwan and many countries, of which myocardial infarction (MI) is the most serious condition. Hyperlipidemia appears to be a significant cause of myocardial infarction, because it causes atherosclerosis directly. In recent years, copy number variation (CNV) has been analyzed in genomewide association studies of complex diseases. In this study, CNV was analyzed in blood samples and SNP arrays from 31 myocardial infarction patients with hyperlipidemia.</p> <p>Results</p> <p>We identified seven CNV regions that were associated significantly with hyperlipidemia and myocardial infarction in our patients through multistage analysis (P<0.001), at 1p21.3, 1q31.2 (<it>CDC73</it>), 1q42.2 (<it>DISC1</it>), 3p21.31 (<it>CDCP1</it>), 10q11.21 (<it>RET</it>) 12p12.3 (<it>PIK3C2G</it>) and 16q23.3 (<it>CDH13</it>), respectively. In particular, the CNV region at 10q11.21 was examined by quantitative real-time PCR, the results of which were consistent with microarray findings.</p> <p>Conclusions</p> <p>Our preliminary results constitute an alternative method of evaluating the relationship between CNV regions and cardiovascular disease. These susceptibility CNV regions may be used as biomarkers for early-stage diagnosis of hyperlipidemia and myocardial infarction, rendering them valuable for further research and discussion.</p

A nationwide survey evaluating the environmental literacy of undergraduate students in Taiwan

The aim of this nationwide survey was to assess undergraduate students’ environmental literacy level in Taiwan. A total of 29,498 valid responses were received from a number of selected colleges and universities in Taiwan, using stratified random sampling method. A total of 70 items were used to assess the environmental literacy and the results revealed that undergraduate students had a relatively low level of environmental knowledge and behavior, while a moderate level of environmental attitudes was attained. The findings also indicated no significant correlations between knowledge and attitudes or between knowledge and behavior. However, a higher level of environmental knowledge correlated significantly with a higher degree of pro-environmental behavior, and a higher level of environmental knowledge correlated with stronger attitudes. The results also suggested that females outperformed the males in all categories. Results from this study could contribute towards further relevant policy discussion and decision-making, curriculum design and development to the improvement of environmental education in the higher education sector