Effect of indomethacin on bile acid-phospholipid interactions: implication for small intestinal injury induced by nonsteroidal anti-inflammatory drugs.

The injurious effect of nonsteroidal anti-inflammatory drugs (NSAIDs) in the small intestine was not appreciated until the widespread use of capsule endoscopy. Animal studies found that NSAID-induced small intestinal injury depends on the ability of these drugs to be secreted into the bile. Because the individual toxicity of amphiphilic bile acids and NSAIDs directly correlates with their interactions with phospholipid membranes, we propose that the presence of both NSAIDs and bile acids alters their individual physicochemical properties and enhances the disruptive effect on cell membranes and overall cytotoxicity. We utilized in vitro gastric AGS and intestinal IEC-6 cells and found that combinations of bile acid, deoxycholic acid (DC), taurodeoxycholic acid, glycodeoxycholic acid, and the NSAID indomethacin (Indo) significantly increased cell plasma membrane permeability and became more cytotoxic than these agents alone. We confirmed this finding by measuring liposome permeability and intramembrane packing in synthetic model membranes exposed to DC, Indo, or combinations of both agents. By measuring physicochemical parameters, such as fluorescence resonance energy transfer and membrane surface charge, we found that Indo associated with phosphatidylcholine and promoted the molecular aggregation of DC and potential formation of larger and isolated bile acid complexes within either biomembranes or bile acid-lipid mixed micelles, which leads to membrane disruption. In this study, we demonstrated increased cytotoxicity of combinations of bile acid and NSAID and provided a molecular mechanism for the observed toxicity. This mechanism potentially contributes to the NSAID-induced injury in the small bowel.

A direct role for secretory phospholipase A2 and lysophosphatidylcholine in the mediation of LPS-induced gastric injury.

Endotoxemia from sepsis can injure the gastrointestinal tract through mechanisms that have not been fully elucidated. We have shown that LPS induces an increase in gastric permeability in parallel with the luminal appearance of secretory phospholipase A2 (sPLA2) and its product, lysophosphatidylcholine (lyso-PC). We proposed that sPLA2 acted on the gastric hydrophobic barrier, composed primarily of phosphatidylcholine (PC), to degrade it and produce lyso-PC, an agent that is damaging to the mucosa. In the present study, we have tested whether lyso-PC and/or sPLA2 have direct damaging effects on the hydrophobic barriers of synthetic and mucosal surfaces. Rats were administered LPS (5 mg/kg, i.p.), and gastric contents were collected 5 h later for analysis of sPLA2 and lyso-PC content. Using these measured concentrations, direct effects of sPLA2 and lyso-PC were determined on (a) surface hydrophobicity as detected with an artificial PC surface and with intact gastric mucosa (contact angle analysis) and (b) cell membrane disruption of gastric epithelial cells (AGS). Both lyso-PC and sPLA2 increased significantly in the collected gastric juice of LPS-treated rats. Using similar concentrations to the levels in gastric juice, the contact angle of PC-coated slides declined after incubation with either pancreatic sPLA2 or lyso-PC. Similarly, gastric contact angles seen in control rats were significantly decreased in sPLA2 and lyso-PC-treated rats. In addition, we observed dose-dependent injurious effects of both lyso-PC and sPLA2 in gastric AGS cells. An LPS-induced increase in sPLA2 activity in the gastric lumen and its product, lyso-PC, are capable of directly disrupting the gastric hydrophobic layer and may contribute to gastric barrier disruption and subsequent inflammation.

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^