39 research outputs found
Thirty years of vaccination in Vietnam: Impact and cost-effectiveness of the national Expanded Programme on Immunization.
INTRODUCTION: Countries like Vietnam transitioning to middle-income status increasingly bear the cost of both existing and new vaccines. However, the impact and cost-effectiveness of the Expanded Programme on Immunization (EPI) as a whole has never been assessed on a country level. METHODS: Data on vaccine-preventable disease incidence and mortality from Vietnam's national surveillance was analysed to estimate the likely impact that vaccination in 1980-2010 may have had. Adjustment for under-reporting was made by examining trends in reported mumps incidence and in case-fatality risks for each disease. The same data were separately analysed using the Lives Saved Tool (LiST) to give an alternative estimate of impact. The financial cost of EPI in 1996-2010 was also estimated from the perspective of service provider. RESULTS: National surveillance data suggests that up to 5.7 million diseases cases and 26,000 deaths may have been prevented by EPI. Analysis using LiST suggests that even more deaths (370,000) may have been prevented by measles and pertussis vaccination alone. The cost-effectiveness of EPI is estimated to be around 27,000 per death prevented. CONCLUSION: Two separate approaches to assessing EPI impact in Vietnam give different quantitative results but a common conclusion: that EPI has made a substantial impact on mortality and represents good value for money
Microscopic Observation Drug Susceptibility Assay (MODS) for Early Diagnosis of Tuberculosis in Children
MODS is a novel liquid culture based technique that has been shown to be effective and rapid for early diagnosis of tuberculosis (TB). We evaluated the MODS assay for diagnosis of TB in children in Viet Nam. 217 consecutive samples including sputum (nâ=â132), gastric fluid (nâ=â50), CSF (nâ=â32) and pleural fluid (nâ=â3) collected from 96 children with suspected TB, were tested by smear, MODS and MGIT. When test results were aggregated by patient, the sensitivity and specificity of smear, MGIT and MODS against âclinical diagnosisâ (confirmed and probable groups) as the gold standard were 28.2% and 100%, 42.3% and 100%, 39.7% and 94.4%, respectively. The sensitivity of MGIT and MODS was not significantly different in this analysis (Pâ=â0.5), but MGIT was more sensitive than MODS when analysed on the sample level using a marginal model (Pâ=â0.03). The median time to detection of MODS and MGIT were 8 days and 13 days, respectively, and the time to detection was significantly shorter for MODS in samples where both tests were positive (P<0.001). An analysis of time-dependent sensitivity showed that the detection rates were significantly higher for MODS than for MGIT by day 7 or day 14 (P<0.001 and Pâ=â0.04), respectively. MODS is a rapid and sensitive alternative method for the isolation of M.tuberculosis from children
Differentiation of breast cancer stem cells by knockdown of CD44: promising differentiation therapy
<p>Abstract</p> <p>Background</p> <p>Breast cancer stem cells (BCSCs) are the source of breast tumors. Compared with other cancer cells, cancer stem cells show high resistance to both chemotherapy and radiotherapy. Targeting of BCSCs is thus a potentially promising and effective strategy for breast cancer treatment. Differentiation therapy represents one type of cancer stem-cell-targeting therapy, aimed at attacking the stemness of cancer stem cells, thus reducing their chemo- and radioresistance. In a previous study, we showed that down-regulation of CD44 sensitized BCSCs to the anti-tumor agent doxorubicin. This study aimed to determine if CD44 knockdown caused BCSCs to differentiate into breast cancer non-stem cells (non-BCSCs).</p> <p>Methods</p> <p>We isolated a breast cancer cell population (CD44<sup>+</sup>CD24<sup>- </sup>cells) from primary cultures of malignant breast tumors. These cells were sorted into four sub-populations based on their expression of CD44 and CD24 surface markers. CD44 knockdown in the BCSC population was achieved using small hairpin RNA lentivirus particles. The differentiated status of CD44 knock-down BCSCs was evaluated on the basis of changes in CD44<sup>+</sup>CD24<sup>- </sup>phenotype, tumorigenesis in NOD/SCID mice, and gene expression in relation to renewal status, metastasis, and cell cycle in comparison with BCSCs and non-BCSCs.</p> <p>Results</p> <p>Knockdown of CD44 caused BCSCs to differentiate into non-BCSCs with lower tumorigenic potential, and altered the cell cycle and expression profiles of some stem cell-related genes, making them more similar to those seen in non-BCSCs.</p> <p>Conclusions</p> <p>Knockdown of CD44 is an effective strategy for attacking the stemness of BCSCs, resulting in a loss of stemness and an increase in susceptibility to chemotherapy or radiation. The results of this study highlight a potential new strategy for breast cancer treatment through the targeting of BCSCs.</p
Complete genome characterization of two wild-type measles viruses from Vietnamese infants during the 2014 outbreak
A large measles virus outbreak occurred across Vietnam in 2014. We identified and obtained complete measles virus genomes in stool samples collected from two diarrheal pediatric patients in Dong Thap Province. These are the first complete genome sequences of circulating measles viruses in Vietnam during the 2014 measles outbreak
Essays in Behavioural Corporate Finance
This thesis consists of three main studies that aim to investigate the impact of managerial characteristics and behaviour in different corporate finance contexts.
The first chapter introduces a novel proxy for managerial conservatism trait by utilising the hand-written signature styles of Chief Executive Officers (CEOs) and Chief Financial Officers (CFOs). The proxy is motivated from psychology research, which proposes that individuals are more conservative if their first names are prone to be abbreviated or missing in their signatures. This chapter documents that conservative CEOs are more likely to make conservative corporate decisions (i.e., more capital expenditures and cash holdings) and avoid risky policies (i.e., less research & development expenses, debt financing and dividend payout). Conservative CFOs are less likely to raise more short-term debt.
The second chapter explores the impact of directorate interlocking networks on stock liquidity. Directorate interlocking is evidenced as an efficient channel by which firms transmit their corporate governance and corporate practices. This chapter employs an approach from sociology to capture network centrality (i.e., a higher centrality indicates more advantages of information acquisition). This study finds that directorate connectedness reduces corporate information opacity (i.e., more efficient corporate governance, better accruals, higher auditing quality and more institutional holdings) and improves stock liquidity.
The third chapter examines the association between board friendliness and corporate social responsibility (CSR). Unlike prior research which captures the similarity in demographic characteristics (e.g., managerial age, tenure and gender), this study aims to gauge the alignment of political ideologies between CEOs and independent directors to proxy for board friendliness. This chapter finds that CEOs in politically friendly boards are less likely to make CSR decisions. This chapter also documents that CEOs whose political ideologies are aligned with the ones of independent directors do not invest in CSR for the benefits of either shareholders or society
Managerial conservatism and corporate policies
This paper investigates how conservative managers make corporate decisions. Motivated by psychology research, we use handwritten signatures (i.e., emotionally restraint disclosure styles) as a proxy for CEO conservatism. We find that firms with conservative CEOs engage more with safer investments (capital expenditures), engage less with risky policies (Research & Development expenses and debt financing), hold more cash, are less likely to pay cash dividends, and more likely to use stock repurchase schemes. We use the same proxy for CFO conservatism. We find that CFO conservatism is a better determinant than CEO conservatism for cash holding and financing policies, but the reverse is true for investment policies. Conservative CFOs prefer long-term debt to short-term debt
Weather Forecast Based on Color Cloud Image Recognition under the Combination of Local Image Descriptor and Histogram Selection
Numerous researchers have used machine vision in recent years to identify and categorize clouds according to their volume, shape, thickness, height, and coverage. Due to the significant variations in illumination, climate, and distortion that frequently characterize cloud images as a type of naturally striated structure, the Local Binary Patterns (LBP) descriptor and its variants have been proposed as feature extraction methods for characterizing natural texture images. Rotation invariance, low processing complexity, and resistance to monotonous brightness variations are characteristics of LBP. The disadvantage of LBP is that it produces binary data that are extremely noise-sensitive and it struggles on regions of the image that are âflatâ because it depends on intensity differences. This paper considers the Local Ternary Patterns (LTP) feature to overcome the drawbacks of the LBP feature. We also propose the fusion of color characteristics, LBP features, and LTP features for the classification of cloud/sky images. Morover, this study proposes to apply the Intra-Class Similarity (ICS) technique, a histogram selection approach, with the goal of minimizing the number of histograms for characterizing images. The proposed approach achieves better performance of recognition with less features in use by fusing LBP and LTP features and using the ICS technique to choose potential histograms
Weather Forecast Based on Color Cloud Image Recognition under the Combination of Local Image Descriptor and Histogram Selection
Numerous researchers have used machine vision in recent years to identify and categorize clouds according to their volume, shape, thickness, height, and coverage. Due to the significant variations in illumination, climate, and distortion that frequently characterize cloud images as a type of naturally striated structure, the Local Binary Patterns (LBP) descriptor and its variants have been proposed as feature extraction methods for characterizing natural texture images. Rotation invariance, low processing complexity, and resistance to monotonous brightness variations are characteristics of LBP. The disadvantage of LBP is that it produces binary data that are extremely noise-sensitive and it struggles on regions of the image that are “flat” because it depends on intensity differences. This paper considers the Local Ternary Patterns (LTP) feature to overcome the drawbacks of the LBP feature. We also propose the fusion of color characteristics, LBP features, and LTP features for the classification of cloud/sky images. Morover, this study proposes to apply the Intra-Class Similarity (ICS) technique, a histogram selection approach, with the goal of minimizing the number of histograms for characterizing images. The proposed approach achieves better performance of recognition with less features in use by fusing LBP and LTP features and using the ICS technique to choose potential histograms