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INTRODUCTION: Cambodia's health equity fund (HEF) is the country's most significant social security scheme, covering the poorest one-fifth of the national population. During the last two decades, the HEF system was scaled up from an initial two health districts to national coverage of public health facilities. This is the first national study to examine the impact of the HEF on the utilisation of public health facilities. METHODS: We first investigated the level of national HEF population coverage and health service use made by HEF eligible members using an administrative HEF operational dataset. Second, through multilevel interrupted time series analysis of routine monthly utilisation statistics during 2006-2013, we evaluated the impact of the HEF on hospital and health centre utilisation. RESULTS: The proportion of HEF beneficiaries using hospital services in a given year (4.6%) appeared to exceed rates in the general population (3.3%). The introduction of the HEF was associated with: a significant level change in the monthly number of consultations at HCs followed by a gradual slope increase in time trend and a significant level change in the monthly number of deliveries. Overall, this was equivalent to a 15.6% net increase in number of consultations and 5.3% in deliveries in the first year. At RHs: a significant level change in the number of RH inpatient cases, followed by a sustained slope increase; a significant slope increase in the number of outpatient consultations and in the overall number of newborn deliveries. Overall, this was equivalent to a 47.9% net increase in inpatient cases, 24.1% in outpatient cases and 31.4% in deliveries in the first year. CONCLUSION: The implementation of the HEF scheme was associated with increased utilisation of primary and secondary care services by the poor.

Mutation, irregular expression and sustained activation of the Transient Receptor Potential Channel, type Melastatin 4 (TRPM4), have been linked to various cardiovascular diseases. However, much remains unknown about the structure of this important ion channel. Here, we have purified a heterologously expressed TRPM4-eGFP fusion protein and investigated the oligomeric state of TRPM4-eGFP in detergent micelles using crosslinking, native gel electrophoresis, multi-angle laser light scattering and electron microscopy. Our data indicate that TRPM4 is tetrameric, like other TRP channels studied to date. Furthermore, the functionality of liposome reconstituted TRPM4-eGFP was examined using electrophysiology. Single-channel recordings from TRPM4-eGFP proteoliposomes showed inhibition of the channel using Flufenamic acid, a well-established inhibitor of TRPM4, suggesting that the channels are functional upon reconstitution. Our characterisation of the oligomeric structure of TRPM4 and the ability to reconstitute functional channels in liposomes should facilitate future studies into the structure, function and pharmacology of this therapeutically relevant channel.

Mutation, irregular expression and sustained activation of the Transient Receptor Potential Channel, type Melastatin 4 (TRPM4), have been linked to various cardiovascular diseases. However, much remains unknown about the structure of this important ion channel. Here, we have purified a heterologously expressed TRPM4-eGFP fusion protein and investigated the oligomeric state of TRPM4-eGFP in detergent micelles using crosslinking, native gel electrophoresis, multi-angle laser light scattering and electron microscopy. Our data indicate that TRPM4 is tetrameric, like other TRP channels studied to date. Furthermore, the functionality of liposome reconstituted TRPM4-eGFP was examined using electrophysiology. Single-channel recordings from TRPM4-eGFP proteoliposomes showed inhibition of the channel using Flufenamic acid, a well-established inhibitor of TRPM4, suggesting that the channels are functional upon reconstitution. Our characterisation of the oligomeric structure of TRPM4 and the ability to reconstitute functional channels in liposomes should facilitate future studies into the structure, function and pharmacology of this therapeutically relevant channel.

INTRODUCTION: Periostin (Postn) is a secreted cell adhesion protein that activates signaling pathways to promote cancer cell survival, angiogenesis, invasion, and metastasis. Interestingly, Postn is frequently overexpressed in numerous human cancers, including breast, lung, colon, pancreatic, and ovarian cancer.METHODS: Using transgenic mice expressing the Neu oncogene in the mammary epithelium crossed into Postn-deficient animals, we have assessed the effect of Postn gene deletion on Neu-driven mammary tumorigenesis.RESULTS: Although Postn is exclusively expressed in the stromal fibroblasts of the mammary gland, Postn deletion does not affect mammary gland outgrowth during development or pregnancy. Furthermore, we find that loss of Postn in the mammary epithelium does not alter breast tumor initiation or growth in mouse mammary tumor virus (MMTV)-Neu expressing mice but results in an apocrine-like tumor phenotype. Surprisingly, we find that tumors derived from Postn-null animals express low levels of Notch protein and Hey1 mRNA but increased expression of androgen receptor (AR) and AR target genes. We show that tumor cells derived from wild-type animals do not proliferate when transplanted in a Postn-null environment but that this growth defect is rescued by the overexpression of active Notch or the AR target gene prolactin-induced protein (PIP/GCDFP-15).CONCLUSIONS: Together our data suggest that loss of Postn in an ErbB2/Neu/HER2 overexpression model results in apocrine-like tumors that activate an AR-dependent pathway. This may have important implications for the treatment of breast cancers involving the therapeutic targeting of periostin or Notch signaling.

Introduction: Periostin (Postn) is a secreted cell adhesion protein that activates signaling pathways to promote cancer cell survival, angiogenesis, invasion, and metastasis. Interestingly, Postn is frequently overexpressed in numerous human cancers, including breast, lung, colon, pancreatic, and ovarian cancer. Methods: Using transgenic mice expressing the Neu oncogene in the mammary epithelium crossed into Postn-deficient animals, we have assessed the effect of Postn gene deletion on Neu-driven mammary tumorigenesis. Results: Although Postn is exclusively expressed in the stromal fibroblasts of the mammary gland, Postn deletion does not affect mammary gland outgrowth during development or pregnancy. Furthermore, we find that loss of Postn in the mammary epithelium does not alter breast tumor initiation or growth in mouse mammary tumor virus (MMTV)-Neu expressing mice but results in an apocrine-like tumor phenotype. Surprisingly, we find that tumors derived from Postn-null animals express low levels of Notch protein and Hey1 mRNA but increased expression of androgen receptor (AR) and AR target genes. We show that tumor cells derived from wild-type animals do not proliferate when transplanted in a Postn-null environment but that this growth defect is rescued by the overexpression of active Notch or the AR target gene prolactin-induced protein (PIP/GCDFP-15). Conclusions: Together our data suggest that loss of Postn in an ErbB2/Neu/HER2 overexpression model results in apocrine-like tumors that activate an AR-dependent pathway. This may have important implications for the treatment of breast cancers involving the therapeutic targeting of periostin or Notch signaling.

When the acronym of ëBRICí was coined in 2001 by Jim OíNeill of Goldman Sachs, it was expected that economic growth rates in India, Brazil and Russia would eventually catch up with that of China. However, China has continued to outperform the other economies in the group, even after it was renamed ëBRICSí to reflect the inclusion of South Africa in 2010. The focus of this chapter is on one of the BRICS economies, namely India. Its aim is to examine from an economic perspective, why Indiaís performance has not lived up to expectations, and comment on the key challenges it faces in meeting them. We begin with some descriptive statistics regarding the progress of the Indian economy since 1990. While it has been growing at a rapid rate since the reforms it introduced in the1990s, there has been a slowdown in its overall GDP growth rates since 2008. The rate of growth experienced in the period 2003ñ07 was an average of 10.5 per cent. However, since the recession following the Global Financial Crisis (GFC) of 2008, the growth rate has fallen. From the period 2008ñ12 it has only registered an average growth rate of 6.5 per cent (World Bank, 2013). This chapter suggests that one of the major factors underpinning this slowdown is the performance of Indiaís agricultural sector. The importance of the agricultural sector is highlighted by the following stylized facts.

Prior studies have failed to examine the spatial dimension of FDI productivity spillovers in transition economies. Using data from China, this article investigates how FDI in one location may affect the productivity of domestic firms in another location. The study finds strong evidence that FDI in the growth pole on the coast adversely affects the productivity of domestic firms in the peripheral interior. There is also some evidence that FDI in the peripheral interior positively affects the productivity of domestic firms in the growth pole on the coast. The findings indicate that the inflows of FDI contribute to the widening regional disparities in transition economies like China.

Prior studies have failed to examine the spatial dimension of FDI productivity spillovers in transition economies. Using data from China, this article investigates how FDI in one location may affect the productivity of domestic firms in another location. The study finds strong evidence that FDI in the growth pole on the coast adversely affects the productivity of domestic firms in the peripheral interior. There is also some evidence that FDI in the peripheral interior positively affects the productivity of domestic firms in the growth pole on the coast. The findings indicate that the inflows of FDI contribute to the widening regional disparities in transition economies like China.

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In today's accelerating world economy, the drive to continually cut costs and focus on core competencies has driven many to outsource some or all of their production. In this environment, improving supply chain execution and leveraging the supply base through effective supplier relationship management (SRM) has become more critical than ever in achieving competitive advantage. It was found that the use of artificial intelligence in the outsourcing function of SRM to identify appropriate suppliers to form a supply network has become a promising solution on which manufacturers depend for products, services and distribution. In this paper, an intelligent supplier relationship management system (ISRMS) using hybrid case based reasoning (CBR) and artificial neural networks (ANNs) techniques to select and benchmark potential suppliers is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, the outsource cycle time from searching for potential suppliers to the allocation of order is greatly reduced.

The design of supplier relationship management to facilitate supplier selection using an integrative case based supplier selection and help desk approach to select the most appropriate suppliers together with their past performance records from a case base warehouse has become a promising solution for manufacturers to identify preferred suppliers and trading partners to form a supply network on which they depend for products, services and distribution. In this paper, an intelligent supplier relationship management system (ISRMS) integrating a company's customer relationship management system, supplier rating system and product coding system by the case based reasoning technique to select preferred suppliers during new product development process is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, it is found that the outsource cycle time from the searching of potential suppliers to the allocation of order, as well as the delay in delivery of goods of suppliers after order allocation, are greatly reduced. In addition, performance of suppliers can be monitored effectively.

In today's accelerating world economy, the drive to continually cut costs and focus on core competencies has driven many to outsource some or all of their production. In this environment, improving supply chain execution and leveraging the supply base through effective supplier relationship management (SRM) has become more critical than ever in achieving competitive advantage. It was found that the use of artificial intelligence in the outsourcing function of SRM to identify appropriate suppliers to form a supply network has become a promising solution on which manufacturers depend for products, services and distribution. In this paper, an intelligent supplier relationship management system (ISRMS) using hybrid case based reasoning (CBR) and artificial neural networks (ANNs) techniques to select and benchmark potential suppliers is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, the outsource cycle time from searching for potential suppliers to the allocation of order is greatly reduced.

The design of supplier relationship management to facilitate supplier selection using an integrative case based supplier selection and help desk approach to select the most appropriate suppliers together with their past performance records from a case base warehouse has become a promising solution for manufacturers to identify preferred suppliers and trading partners to form a supply network on which they depend for products, services and distribution. In this paper, an intelligent supplier relationship management system (ISRMS) integrating a company's customer relationship management system, supplier rating system and product coding system by the case based reasoning technique to select preferred suppliers during new product development process is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, it is found that the outsource cycle time from the searching of potential suppliers to the allocation of order, as well as the delay in delivery of goods of suppliers after order allocation, are greatly reduced. In addition, performance of suppliers can be monitored effectively.

Item does not contain fulltext

Item does not contain fulltext

In today's accelerating world economy, the drive to continually cut costs and focus on core competencies has driven many to outsource some or all of their production. In this environment, improving supply chain execution and leveraging the supply base through effective supplier relationship management (SRM) has become more critical than ever in achieving competitive advantage. It was found that the use of artificial intelligence in the outsourcing function of SRM to identify appropriate suppliers to form a supply network has become a promising solution on which manufacturers depend for products, services and distribution. In this paper, an intelligent supplier relationship management system (ISRMS) using hybrid case based reasoning (CBR) and artificial neural networks (ANNs) techniques to select and benchmark potential suppliers is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, the outsource cycle time from searching for potential suppliers to the allocation of order is greatly reduced.

The design of supplier relationship management to facilitate supplier selection using an integrative case based supplier selection and help desk approach to select the most appropriate suppliers together with their past performance records from a case base warehouse has become a promising solution for manufacturers to identify preferred suppliers and trading partners to form a supply network on which they depend for products, services and distribution. In this paper, an intelligent supplier relationship management system (ISRMS) integrating a company's customer relationship management system, supplier rating system and product coding system by the case based reasoning technique to select preferred suppliers during new product development process is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, it is found that the outsource cycle time from the searching of potential suppliers to the allocation of order, as well as the delay in delivery of goods of suppliers after order allocation, are greatly reduced. In addition, performance of suppliers can be monitored effectively.