The recent primary care policy debate in Australia has centred on access to primary medical  services. In Australia, access is heavily influenced by Commonwealth Government patient rebates that provide incentives for general practitioners not to charge copayments to patients (bulk billing). A steady decline in key access indicators (bulk billing) has led the Howard Government to introduce a set of changes that move Medicare from a universal scheme, to one increasingly targeted at providing services to more disadvantaged Australians. In doing so, another scene in the story of the contest between universal health care and selective provision in Australia has been written. This paper explores the immediate antecedents and consequences of the changes and sets them in the broader context of policy development for primary care in Australia. Primary health care and community care can be thought of as a set of health programs and services. Most discussions of the primary health and community care services sector suggest that it has the following characteristics: (1) It is the first point of contact with the health system. This may occur through general practice, community health services, and pharmacies. There is also some overlap between primary care and hospital emergency departments, particularly for less complex and intensive presentations. (2) Services are provided in community and ambulatory settings and at home. (3) There is an emphasis on continuing relationships between service providers and consumers over extended periods of time. (4) Services have a more comprehensive and holistic approach. (5) There is an emphasis on early detection and illness prevention services such as maternal and child health programs and population health programs including health promotion.Primary health and community care is the most visible and commonly used part of the health system. In 1999–00 the Commonwealth provided approximately $6 billion through the Commonwealth Medical Benefits and Pharmaceutical Benefits Schemes. States and Local Government provided approximately $1.8 billion for 'community and public health' which includes allied health, counselling, nursing and a range of primary and secondary prevention and health promotion programs. The Commonwealth, through direct outlays ($6 million) and private health insurance premium rebates ($97 million), also provided $103 million for dental services, with the States and Territories contributing $305 million. This does not include the substantial funds committed to the various forms of community support for people with disabilities, chronic illness and mental illness [Primary health and community care services face unique challenges. Over the past three decades primary health services have come under significant pressure to address a more complex and diverse range of community needs.Deinstitutionalisation, the introduction of new health and information technologies, the increasing prevalence of chronic disease and more general social and economic trends have had a significant impact on primary health and community support services. This has resulted in concerns about the equity, quality and efficiency of services and programs. Arguably, there is a need for a national primary health care policy in Australia. One that would address system integration, care pathways and team practice, work force development, payment arrangements, governance, performance management and accountability. However, current Commonwealth reforms are focused on important, but relatively, narrowly focused solutions to the decreasing affordability and access for general medical services. This article focuses primarily on the recent debate that surrounds this issue.Medicare is a Commonwealth Government, tax funded, social insurance scheme that provides rebates for general (primary) and specialist medical services and optometry. In Australia, it is the principal national program for ensuring equitable access to primary medical services. Over the last two years there has been a fiercely contested debate about the future of Medicare.Medicare was introduced to provide universal access to affordable medical care. Up until recently Medicare simply provided a rebate of 85% of the Commonwealth Government determined schedule fee for medical and diagnostic services. Practitioners were free to charge patients a copayment as well. Where they did not apply a copayment, they could bill the Commonwealth for the rebate and receive bulk payments direct from the Commonwealth for these services, thereby avoiding administrative costs and delay. This payment method, which became known as bulk billing, ensured that services were effectively free to the patient at the point of service.Medicare has been very successful, particularly for general practice services. It is strongly supported by the Australia community because it provides affordable access to medical services. Despite historical resistance by the Australian Medical Association, it has been widely supported by practitioners because it provides them with a universal, simple and predictable revenue stream.Bulk billing increased steadily from the introduction of Medicare in 1984/85 to approximately 70% in the mid-1990s. Bulk-billing rates for GP services have generally been about 10% higher than the overall bulk-billing rates over the last decade, reaching a plateau of about 80% in the mid-1990s. They declined significantly after 2000. Average GP bulk billing fell to 68% by September 2003. GP bulk billing rates are now similar to the overall CMBS bulk billing rates for all services [As bulk billing rates declined, disquiet and concern about access to medical services rose amongst stakeholder interests. More generally, the overall decline in bulk billing came on top of considerable disparity in equity of access between rural and urban settings. Bulk billing rates in inner city areas with high per capita GP ratios were 30% higher than those in rural settings with low per capita ratios. A number of remote rural areas had difficulty attracting any GPs at all.Analysis of the reasons for the decline in bulk billing and the disparities between rural and metropolitan settings suggest a strong relationship between the supply of GPs and the capacity to charge copayments and the importance of the steady decline in the relative value of Commonwealth rebates for GP services over time.There is considerable evidence that GPs manage demand for their services to maintain their income . As the In the decade to 2003, changes to GP training, migration and demographic ageing lead to a stabilization and decline in the supply of GP services. Over the same period, the relative value of Medicare rebate income for GP services fell by about 10 percent compared with average weekly ordinary time earnings. A decline that was probably even greater when compared to specialist incomes. In response, GPs began to experiment with price increases (co-payments) to improve their relative incomes .Interestingly, bulk billing rates in relatively under supplied rural settings remained relatively stable at about 50% of consultations. This is about the level of consultations one would expect people on low incomes, who are eligible for concessional welfare benefits, to use. A finding that suggests that patient capacity to pay sets a 'floor' bulk billing rate at about this level .It is worth noting that many of these effects were predictable from the reforms to General Practice introduced in the early 1990s. In particular, tight management of GP supply through changes to training programs and restrictions on overseas trained medical practitioners were introduced in order to reduce growth in aggregate Medicare expenditure. However, the reforms recognised that a move away from fee for service payment would also be required in the longer term. To this end a Better Practice Program to pay GPs on a per capita basis was introduced.Over time, it was intended that a significant proportion of Medicare payments would be made by practice based, per capita payments. Progressively this would have allowed a shift toward more comprehensive, integrated practice and a greater focus on quality and preventive services. However, while the supply of GPs was successfully constrained, per capita payments remained a marginal component of the payment system.In response to concerns about the fall in the bulk billing rate, the Commonwealth Government proposed a "Fairer Medicare" package in April 2003. The package introduced a participating practice scheme. GP practices that agreed to charge a no gap fee to concessional patients were to be eligible for increased Medicare rebates for these patients. The level of the proposed increase for the rebate was $1 in metropolitan city practices, $2.95 in non-metropolitan city practices, $5.30 in rural centre practices, and $6.30 in outer rural and remote areas.Participating practices were to continue to have the capacity to determine fees for non-concession cardholders, including the option of bulk billing. However, if they chose not to bulk bill these patients, they were to be able to charge the patient the co-payment and claim the Medicare rebate direct from the Health Insurance Commission through HIC online billing facilities. Effectively, non-concession cardholders were to be charged a gap payment thereby avoiding the transaction costs involved in claiming a rebate through the Medicare scheme themselves.A new MBS safety net was to be available for those covered by concession cards with out-of-pocket costs greater than $500 in a calendar year. Charges in excess of the scheduled fee were to be included, as were the costs of specialist and diagnostic services. Eighty per cent of out-of-pocket costs above the $500 threshold were to be met through this safety net.Private health insurers were to be able to offer insurance coverage for the cumulative cost of out-of-hospital medical services over $1,000 for a family in a calendar year. This included costs above the scheduled fee across a range of out-of-hospital services, including GP and specialist consultations and diagnostic tests. The Commonwealth estimated that insurance products for this coverage were likely to cost around $50 per year for families, and the 30% private health insurance rebate was to apply to these products.The Government's package also included proposals to introduce additional medical school places, additional GP training places, additional nurses and allied health professionals in general practice, and measures for veterans.The Fairer Medicare package resulted in considerable debate and criticism, much of which was considered by the Senate Select Committee on Medicare . In part• Equitable access to general practice services regardless of income or geography is fundamental to good health care.• GP income from bulk billing had not kept pace with increases in average weekly ordinary time earnings and this had contributed to declining bulk billing rates and increased out of pocket charges.• Shortages in the supply of GPs are emerging as result of compositional changes in the workforce, changes in practice patterns and population ageing.• The Commonwealth's 'Fairer Medicare' proposals were inconsistent with the principles of Medicare.• The differential rebate payments for concessional patients were unnecessary because these patients were already largely receiving bulk billed services• The introduction of the new safety net arrangements creates a two tier system of access to GP servicesIt became apparent that the Senate would not pass the legislation required to enact the Commonwealth's package. Consequently, the Commonwealth presented its 'MedicarePlus' extensions and revisions to the original proposal in November 2003 . This paThe MedicarePlus proposals dropped the participating practice scheme. Instead the Commonwealth proposed to increase the rebate for all concessional patients by $5 in metropolitan areas and $7.50 in remote, rural and regional areas (including the State of Tasmania). The increased rebate was also extended to children under 16. The safety net provisions were modified to provide an 80% rebate for out of hospital medical costs for concessional patients and those whose income fell below specified tax thresholds after $300 of out of pocket expenses and after $700 for the remainder of the population.Other aspects of the original proposal were largely retained and extended. These included training places for GPs, medical graduates and nurses. Additionally, it was proposed to introduce a Medicare Benefits Schedule item for nursing support in general practice and improved internet access and online billing for GPs. MedicarePlus also provides rebates for up to five allied health consultations delivered to patients with a chronic condition or complex care needs, for and on behalf of a GP. Similarly, dental treatment care plans will be funded for these patients where they have significant dental problems that exacerbate their condition. The total estimated cost for MedicarePlus to 2006/07 was estimated at $2.85 billion.Initial reactions to the Commonwealth's proposals were mixed. A number of patient and provider groups have criticized the new arrangements as undermining the principle of universality that underpins Medicare. Criticisms have also focused on the narrow focus of MedicarePlus on fees for general practitioners.More specifically, MedicarePlus is likely to have differential effects on affordability and access to GP services in rural and metropolitan settings. In metropolitan settings, the introduction of a $5 differential rebate for bulk billing concessional payments is sufficient to increase net GP incomes to about the AWOTE relativities that applied prior to the decline in bulk billing.However, with current levels of bulk billing still at over 65% in metropolitan areas, virtually all concessional patients are already bulk billed. The proposal is therefore subject to substantial dead weight loss. No incentives to bulk bill non concessional patients  are included.In metropolitan areas, the gap between the average Medicare rebate and the average patient billed service is around $13 for patients not covered by the differential rebate, compared to $8 for concessional patients and children under 16. Within system constraints, GP incomes are optimized by bulk billing concessional patients and children under 16 and charging copayments for other patients. Doing so also largely addresses patient capacity to pay issues. In the absence of major changes to supply or GP costs, it is therefore likely that bulk billing rates in metropolitan areas will continue to decline over time, until they stabilise at around the level of services for concessional patients plus non concessional children under 16 (around 60% in metropolitan areas, assuming children under 16 have average population consultation rates).The proportion of children is highest in outer metropolitan regions and lowest in the inner city. Bulk billing rates have declined most in outer metropolitan areas. It is therefore plausible that this measure will have the greatest differential impact in outer metropolitan regions.In rural settings, where there are GP shortages, the differential rebate (which is higher than in metropolitan settings) could substantially increase GP incomes. However, GP supply factors ensure GPs have considerable capacity to increase copayments within the limits of patient capacity to pay. In general, bulk billing rates in rural settings are now at or below the consultation rate for concessional patients. The new arrangements are therefore likely to protect bulk billing rate for concessional patients and are likely to see the rate increase to the level of concessional consultations (around 55 – 60%).The effect of differential rebates for non concessional children under 16 on overall bulk billing rates is less clear in rural settings. With the increased rebate, there remains a gap of approximately $5.50 between the new rebate and the average patient billed service. As for metropolitan settings, there are no additional incentives to bulk bill other non concessional patients. Given the greater capacity to charge copayments, this measure may be less successful in encouraging bulk billing than in metropolitan areas.The safety net provisions in MedicarePlus have significant inflationary potential for out of hospital medical service fees. Concessional patients and those who qualify for Family Tax Benefit A are eligible for an 80% rebate on out of hospital costs once they incur $300 of out of pocket costs. There is no cap on the rebate under the safety net. Average out of pocket costs for patient billed GP services are currently about $13. The safety net is therefore reached in 20–25 consultations. The safety net provisions will be invoked more quickly when specialist medical practitioners, diagnostic imaging services and pathology are required. Average copayments are two or three times higher for specialist medical practitioners than for GPs.Effectively, the introduction of the safety net removes constraints on medical practitioners associated with concerns about patient capacity to pay. This introduces moral hazard for practitioners and consumers. Practitioners have incentives to increase their fees and provide more services than necessary knowing the safety net will protect patients. Patients have incentives to consume more services than are necessary because they are effectively insured by the safety net.However, the initial threshold and value of copayments act as balancing disincentives for utilization. Clearly if the initial threshold and the copayments were less, the hazard would be greater and vice versa. This trade off is likely to impact differently depending on need, capacity to pay and supply factors.For example, there may be paradoxical adverse effects for patients with significant ongoing health costs who are currently bulk billed because GPs and specialists have concerns about their capacity to meet aggregate out of pocket costs over time. This is particularly true for aged pension recipients with chronic illness. With the introduction of the safety net, the potential for incurring unmanageable costs is significantly reduced and therefore bulk billing rates for this group may decline. Whether effects like these are experienced in practice will depend on factors such as the real value of GP rebates, patient need, capacity to pay, GP supply and regulatory constraints.Overall, the design features of the Howard Government recent changes to Medicare are intended to, and will produce a two tier system. Access to primary medical services for people on low incomes will be relatively well protected, but those above the income threshold will see a steady decline in bulk billing and an increase in out of pocket costs for these services. Additionally, the poorly designed safety net will have inflationary consequences.The policy and political contest around Medicare has an extended pedigree. The conservative Liberal/National Party Coalition has long held the position that government should primarily provide health services for those who are unable to provide for themselves and that those who are able to make their own way should do so, particularly by taking out private health insurance. From this perspective the role of government is to provide an appropriate regulatory environment, incentives and sanctions to take up private insurance and a targeted safety net for the disadvantaged. Their preferred model was developed and refined in the 1950s and 1960s during the period of the Menzies Government and reintroduced in stages during the late 1970s and early 1980s by the Fraser Government [On the other hand, the Australian Labor Party has advocated tax funded, universal access to publicly funded health care provided on the basis of need, rather than capacity to pay. The Whitlam Government settled the basic architecture of Labor's approach in the early 1970s. Setting aside the brief flirtation with a national community health program for primary care, it established a universal system of public hospital access through the States and a tax funded, social insurance scheme to underwrite equitable access to medical and related services.Notwithstanding Howard Government claims of strong support for Medicare, the pendulum has now swung a considerable distance back toward the traditional Liberal/National Party preferred model. If history is a guide, now that the incentives to take out private health insurance and the safety net is in place, the next steps are regulatory mechanisms to exclude higher income earners from accessing publicly funded health services.While debates about access and equity are critical, they are only part of the overall picture. Recontesting the basic access and equity principles of the health system every decade or so misses a number of important emerging issues.There is now emerging evidence that closer integration of clinical decision-making and purchasing for enrolled populations in primary care settings through funds pooling and local agreements and contracts has the potential to increase innovation, reduce costs and improve outcomes. These principles are being explored or actively implemented in a number of countries comparable to Australia, including the United Kingdom and New Zealand .There is clearly a need to reconsider the development of a national policy for primary health and community support services. Such a policy might include the following elements to address the issues which have been discussed above:• National primary health and community care goals and objectives. For example, these might broadly set out equity, efficiency and quality criteria for the Australian primary health and community support system.• National performance indicators. For example, these indicators could be used to report on and benchmark the quality, access, efficiency and utilisation of the primary health and community support system and its impact on acute, sub acute and residential care.• Population based planning, allocation and monitoring. For example, funding allocation models and system governance arrangements based on the health care needs of geographically defined residential populations  that promote continuity of care and service integration could be considered.• Coordinated service pathways for health issues and conditions. For example, consistent best practice models linking prevention, early intervention, primary care, acute care, rehabilitation and community support should be developed for all major chronic diseases, mental illness and alcohol and drug problems.• Payment systems. For example a program to develop integrated payment models and systems for primary and community support services could be established and linked to Commonwealth/State agreements (e.g. AHCAS, HACC) and own purpose funding streams. This might include consideration of capitated, case based, and contract funding to replace or compliment existing arrangements for primary care services.• National workforce planning and analysis for primary health and community support services.• A national evaluation, research and development program in primary health and community support services.• National planning and priority setting processes for primary health and community care to ensure greater alignment of Commonwealth and State priorities.


Wolbachia have a thing against males. A member of one of the most diverse groups of bacteria, called Proteobacteria, this parasitic “endosymbiont” lives inside the reproductive cells of a wide variety of the nearly 1 million species of arthropods, including insects, spiders, and crustaceans. It has also been found in worms. Wolbachia's preferred habitat is the cytoplasm of its host's gametes. Since sperm have very little cytoplasm, Wolbachia seek out the company of females, securing its survival by hitching a ride to the next generation in the cytoplasm of the mother's eggs. Wolbachia's effects range from beneficial to pathological, depending on which species infects which invertebrate host, but since most species are not beneficial, Wolbachia infections often turn out badly if the host is male. On the other hand, if female, the host could very well live longer, produce more eggs, and have higher hatching rates than its noninfected cousins—thereby facilitating Wolbachia's transmission from mother to offspring.Wolbachia have evolved an impressive repertoire of “reproductive parasitic” strategies to adapt its host's physiology to its own advantage. One strategy involves inducing “cytoplasmic incompatibility” between sperm and egg, which in effect uses infected males to keep uninfected females from producing viable offspring. Another causes infected females to reproduce asexually, creating a new generation of infected clones. Another turns developing male embryos into females. And, in a pinch, some Wolbachia simply kill developing males. The biochemical mechanisms that trigger different strategies in different hosts are unclear, however, in part because it's so far been impossible to cultivate sufficient quantities of these obligate endosymbionts (that is, intracellular species that cannot survive outside their host). But now that Scott O'Neill, Jonathan Eisen, and colleagues have sequenced the complete genome of one strain of Wolbachia pipientis, scientists investigating the biology and evolution of Wolbachia–host interactions have a valuable new research tool. The strain they sequenced, W. pipientiswMel, lives inside the fruitfly Drosophila melanogaster, the favorite model organism of geneticists for nearly 100 years. This strain causes cytoplasmic incompatibility in its host.wMel genome, the O'Neill and Eisen groups note, is strikingly different from any other obligate intracellular species. While its genome is compact, it nonetheless contains large amounts of repetitive DNA and “mobile” DNA elements. Mobile genetic elements, as the name implies, are DNA sequences that move around the genome and are often acquired from other species. Most of the repetitive and mobile elements in Wolbachia do not appear in other α-Proteobacteria species and were probably introduced some time after Wolbachia split off from its evolutionary ancestors. Wolbachia, unlike other obligate intracellular bacteria, seem quite amenable to incorporating foreign DNA, which the authors speculate was introduced by the bacteria-infecting virus called phage.The structure of the Wolbachia genome sheds light on the mechanisms that might help the parasite manipulate the host cell's physiology to its own advantage. One likely bacterial weapon for host exploitation is the abundance of predicted genes encoding ankyrin repeat domains, amino acid sequences characteristic of proteins important for protein–protein interactions in eukaryotes (organisms with nuclei, which bacteria lack). In bacteria, ankyrin repeats might regulate host cell-cycle pathways, which one wasp-infecting Wolbachia strain modifies to induce cytoplasmic incompatibility. Other molecular interactions between wMel and its host, the researchers propose, might also rely on proteins with these ankyrin repeats.Analysis of the Wolbachia genome also provides insight into mitochondrial evolution. It is widely believed that these intracellular energy-metabolizing centers were once free-living bacteria belonging to the α-Proteobacteria group, though it's not clear which branch of the α-Proteobacteria tree they inhabit. Complete genome analysis of various α-Proteobacteria—including wMel, the first non-Rickettsia species sequenced in the Rickettsiales group—provides no evidence that mitochondria are more related to Rickettsia species than to Wolbachia, as was previously thought. In fact, further analysis failed to consistently connect mitochondria to any particular species or group within the α-Proteobacteria.The Wolbachia genome seems to raise as many issues as it settles, biologists studying a wide range of problems—from the evolution and biology of Wolbachia and endosymbiont–host interactions to the origin of mitochondria—have a valuable new tool to explore their questions. The Wolbachia genome will also provide important molecular guidance for efforts to suppress insect pests and control filariasis, a human disease caused by worms. Since beneficial Wolbachia live in both insect and worm, applying antibiotics to target the Wolbachia will ultimately kill the insect pest and infecting worm, which both depend on the bacteria to survive.While the information hidden in the


We investigated these factors in the fibrotic response to bleomycin of p47Mice are administered by intranasal instillation of 0.1 mg bleomycin. Either 24 h or 14 days after, mice were anesthetized and underwent either bronchoalveolar lavage (BAL) or lung removal.phox -/- mice. At day 1, the bleomycin-induced acute inflammatory response (increased neutrophil count and MMP-9 activity in the BAL fluid) was strikingly greater in KO than wild-type (WT) mice, while IL-6 levels increased significantly more in the latter. Hydroxyproline assays in the lung tissue 14 days after bleomycin administration revealed the absence of collagen deposition in the lungs of the KO mice, which had significantly lower hydroxyproline levels than the WT mice. The MMP-9/TIMP-1 ratio did not change at day 1 after bleomycin administration in WT mice, but increased significantly in the KO mice. By day 14, the ratio fell significantly from baseline in both strains, but more in the WT than KO strains.BAL cells from bleomycin treated WT mice showed enhanced ROS production after PMA stimulation, whereas no change was observed with BAL cells from p47These results suggest that NADPH-oxidase-derived ROS are essential to the development of pulmonary fibrosis. The absence of collagen deposition in KO mice seems to be associated with an elevated MMP-9/TIMP-1 ratio in the lungs. This finding highlights the importance of metalloproteinases and protease/anti-protease imbalances in pulmonary fibrosis. Pulmonary fibrosis is a severe chronic disease with various causes and poor prognosis. Its main histological features include lesions of the alveolar septa, fibroblast and myofibroblast proliferation in lung parenchyma, abnormal reepithelialization, and excessive extracellular matrix macromolecule deposition -3. Lung Metalloproteinases (MMPs) and their specific inhibitors, the tissue inhibitors of MMPs (TIMPs), are the hallmark of this fibrogenic microenvironment. MMPs are key enzymes that regulate tissue remodeling through turnover of the extracellular matrix in both normal and pathological conditions (for review see ). They pStrong evidence indicates that various MMP/TIMP imbalances are crucial elements in the fibrogenic process. Several authors suggest that a "nondegrading microenvironment" induces fibrogenicity, that is, more specifically, that various events cause TIMP-1 levels to rise in lung tissue, which in turn lowers MMP/TIMP ratios ,11,12. Bphox subunit of NADPH-oxidase [Further study is needed to illuminate the pathway that leads from lung injury, associated with ROS and acute inflammation, to initiation of the fibrogenic process, which involves remodeling mediators such as MMPs and TIMPs. The aim of the present study was to investigate the involvement of the ROS released by inflammatory cells during the development of pulmonary fibrosis and to consider the consequence on MMP/TIMP balances. We therefore examined the fibrogenic response to bleomycin administration in mice deficient for the p47-oxidase  and anal®, 2 mg/mL) from Janssen-Cilag (Issy-les-Moulineaux, France); acrylamide, sodium dodecyl sulfate (SDS), Tris, and BSA from Eurobio (Les Ulis, France); ELISA kits for IL-6, TIMP-1, and pro-MMP-9 detection from R&D Systems (Minneapolis, MN, USA); formaldehyde from Merck (Darmstadt, Germany); isopentane from Prolabo (Fontenay-sous-Bois, France); a low-range weight marker for SDS-PAGE from Biorad (Munich, Germany); and an ABEL® chemiluminescence kit for measurement of in vitro ROS release from Knight Scientific Limited (Plymouth, UK).This study used the following materials, from the manufacturers mentioned: bleomycin sulfate from Bellon Laboratories (Montrouge, France); gelatin, Triton X-100, Coomassie Brilliant Blue, EDTA, Tween 20 solution, hydroxyproline, and trypan blue from Sigma (St Louis, MO, USA); May-Grünwald and Giemsa stains from RAL (Paris, France); sodium pentobarbital from Sanofi Santé Animale (Libourne, France); etomidate (Hypnomidatephox +/+ "wild-type" (WT) and p47phox -/- "knockout" (KO) mice (origin: LHD/NIAID/NIH, Bethesda, MD, USA) with C57BL/6J backgrounds [Ten week-old p47kgrounds  were houPulmonary fibrosis was induced by intranasal (i.n.) instillation (under etomidate anesthesia, 15 mg i.p.) of 0.1 mg bleomycin sulfate in saline solution (50 μL/mouse). Control mice received saline vehicle only. Either 24 h or 14 days after i.n. administration, mice were quickly anesthetized by an i.p. injection of sodium pentobarbital (60 mg/kg) and underwent either bronchoalveolar lavage (BAL) or lung removal. These samples were stored at -80°C until either hydroxyproline measurement or homogenization for zymography.® . Red blood cells were eliminated by adding 3 mL of distilled water for 30 seconds and then 1 mL of KCl 0.6 M onto the pellets. After centrifugation (600 g for 10 min, 4°C), supernatant was eliminated and the cells were suspended in 1 mL of PBS. They were then cytospun at 700 rpm for 10 minutes (Cytospin 3 ®, Thermo Shandon, Ltd, Astmoor, United Kingdom) and stained with the May-Grünwald Giemsa method. Differential cell counts of 200 cells used standard morphological criteria.Mice were anesthetized with an i.p. administration (20 mL/kg) of sodium pentobarbital 0.6%. The BAL protocol called for washing the airways 10 times with 0.5 mL of 0.9% NaCl solution at 37°C with a 1 mL syringe. The BAL fluid was centrifuged (600 g for 10 min, 4°C), and the supernatant of the first two fractions (1 mL) divided into aliquots and frozen at -80°C until analysis. The cell pellets were then pooled with the last fractions. Total cells were counted with a Coulter Z2® detection kit.After in vitro stimulation with phorbol 12-myristate 13-acetate (PMA), 0.8 μM, ROS production was assayed with a chemiluminescence technique that used the ABELAt day 14, following BAL processing, lungs were removed and homogenized with an adapted grinder (Fast-Prep FP 120 cell disrupter, QBiogene Inc., Illkirch, France). Lung tissue homogenates were then stored at -80°C until analysis.2, 2 μM ZnCl2, pH = 8. The gels were stained with Coomassie Brilliant Blue in a solution of 25% ethanol-10% acetic acid in water and rinsed in an identical solution. Gelatinase activity appeared as clear bands against blue background. We used recombinant protein molecular weight markers (20 kDa-112 kDa) to estimate the molecular weights of the gelatinolytic bands. Relative enzyme amounts were quantified by measuring the intensity of the bands with a densitometric analyzer . Results were expressed as a percentage of the band of migration of one control BAL sample loaded onto each gel. This sample was used as an internal standard to allow further comparisons between gels.Since MMPs can degrade gelatin, zymographic techniques were used to detect MMPs in both BAL (day 1 and day 14) and lung homogenates (day 14). In nonreducing conditions and in the presence of SDS, as previously described , aliquotThe amounts of total IL-6, TIMP-1, and pro-MMP-9 were determined with ELISA methods, performed according to the manufacturer's recommendations. Assay sensitivity was 31 pg/mL for TIMP-1, 15 pg/mL for IL-6, and 8 pg/mL for pro-MMP-9.Lung tissue was lyophilized, weighed, ground to a fine powder with a mortar and pestle, homogenized in PBS pH = 7.4, and divided into aliquots. After hydrolysis for 45 min in NaOH 2 N, the hydroxyproline content was assayed in duplicate aliquots, as previously described .Results were expressed as means ± SEM. The differences between the groups for treatment and strain effects were analyzed with a nonparametric Mann-Whitney U test. Correlations between the BAL analysis data and the MMP levels and activity were assessed with the nonparametric Spearman correlation test. For each analysis, P values less than 0.05 were considered to be statistically significant.in vitro with PMA  mice.Zymography identified the following gelatinolytic bands as MMP activity: pro-MMP-9 (105 kDa), MMP-9 (86 kDa), pro-MMP-2 (70 kDa), and MMP-2 (64 kDa). At day one, pro-MMP-9 activity was significantly higher in the BAL of bleomycin-treated KO mice than in that of their bleomycin-treated WT counterparts, which in turn was significantly higher than in the control mouse BAL figure . At day At one day and 14 days after bleomycin administration, MMP-2 activity was observed in both its latent (70 kDa) and active (64 kDa) forms figure . AlthougMMP activity was also evaluated at day 14 in lung homogenates figure . HomogenWe also evaluated pro-MMP-9 as well as TIMP-1 with ELISA table . The resTable phox subunit of the NADPH oxidase complex do not develop pulmonary fibrosis after intranasal administration of bleomycin. It also suggests that an imbalance of the molar MMP-9/TIMP-1 ratio may influence the fibrogenic process in this model.This study shows that mice deficient in the p47phox-/- KO mice. Unlike antioxidant compounds, which nonspecifically target all ROS sources in the tissue, knocking out the p47phox subunit of the NADPH oxidase complex shuts down only the main pathway of phagocytic ROS production. In this study, in vitro PMA stimulation of BAL cells from KO mice produced no detectable ROS, while BAL cells from WT mice did produce ROS, as previous studies of circulating neutrophils from these mice have shown [Several studies previously reported that antioxidant treatment attenuates the bleomycin-induced oxidative burden and subsequent pulmonary fibrosis ,8,17. Move shown .Hydroxyproline content did not increase in the lungs of these KO mice. This finding reveals the absence of fibrosis and thus provides strong evidence that phagocytic ROS production is an important component of the fibrogenic environment.in vivo previously described in such KO mice [Although no ROS production was detected in KO mice, their BAL gave evidence of an acute inflammatory response, as did that from WT mice: bleomycin administration elicited acute inflammation, characterized by an influx of neutrophils and associated with increased pro-MMP-9 activity. Moreover, the response of the KO mice to the bleomycin resembled the abnormal "exuberant" inflammation  KO mice ,20,21. I KO mice .phox-/- KO mice [This acute inflammation was accompanied by significantly elevated IL-6 levels in the BAL fluids of both strains of mice on the day after bleomycin administration, levels significantly higher in WT than KO mice. Given that IL-6 is secreted primarily by mononuclear cells, specifically macrophages, the difference between strains suggests that these cells are activated more weakly in the KO than in the WT mice. Moreover, in SP-D -/- alveolar macrophages, the NADPH oxidase inhibitor apocynin inactivates NF-kappa B, the transcription factor that regulates numerous proinflammatory responses, including IL-6 release . Similar KO mice . This woMMP induction, assessed by gelatinase release, has been reported in various cases of pulmonary fibrosis in human and experimental models ,25,26. WIt is thus difficult to reach a definitive conclusion at this time about the exact function of MMPs. They play a role in promoting tissue remodeling and counterbalancing excessive matrix deposition, but may also facilitate tissue damage and disruption. Their involvement in bleomycin-induced pulmonary fibrosis has been demonstrated with the inhibition of collagen deposition by bastimastat, a nonselective MMP-inhibitor . CompletIncreased TIMP-1 expression has been observed in lung extracts and in BAL fluids after bleomycin administration and after the transfer of the active TGF-beta gene to "fibrosis-prone" C57BL/6 mice ,14. In hInterestingly, in our study, the pro-MMP-9/TIMP-1 ratio was significantly higher for KO than WT mice, at both day one and day 14. At day 1 this was due to the lower MMP-9 level and higher TIMP-1 level in the BAL from WT mice, and at day 14, only to the latter. The correlation of these levels with differences in hydroxyproline levels in the lungs of bleomycin-treated mice strongly suggests that a reduced molar pro-MMP-9/TIMP-1 ratio in BAL fluid is associated with collagen deposition, beginning as early as the inflammatory events at day 1 after bleomycin administration.phox-/- KO mice could provide great amount of other kind of protease, such as serine proteases. Indeed, neutrophil elastase was shown to have an impact on the severity of bleomycin-induced pulmonary fibrosis [The usefulness of the pro-MMP-9/TIMP-1 ratio as a marker of fibrosis nonetheless requires discussion. Although a molar ratio appears to play a protective role against fibrotic changes, MMP-9 is considered primarily to be an inflammatory mediator released by leukocytes during acute inflammatory events to facilitate their progression across the basement membrane . Moreovefibrosis ,35phox-/- KO mice to produce large quantities of ROS via the NADPH oxidase pathway inhibits the development of bleomycin-induced pulmonary fibrosis. This inhibition is associated with changes in IL-6 production and in the molar MMP-9/TIMP-1 ratio, both probably key factors in airway remodeling and fibrosis. These rapidity of these differences after bleomycin administration suggests that early inflammatory events and remodeling events may establish a favorable environment for further chronic fibrogenic processes.In summary, this study demonstrates that the inability of phagocytes from p47BAL: Bronchoalveolar lavageIL: interleukinKO: knock outMMP: matrix metalloproteinaseTIMP: tissue inhibitor of metalloproteinaseROS: reactive oxygen speciesWT: wild typeBM, SN, OL, IG:and EB have made substantial contributions to acquisition and analysis of dataBM, SN, EB and VL have made substantial contributions to conception and designBM, EB and VL have been involved in drafting the articleJMP and CPB have been involved in revising it critically for important intellectual content


Rhus verniciflua Stokes. It has long been used as a food additive in Korea and as an herbal medicine throughout Asia. Recently, butein has been shown to suppress the functions of fibroblasts. Because fibroblasts are believed to play an important role in promoting the growth of breast cancer cells, we investigated the ability of butein to inhibit the clonogenic growth of small numbers of breast cancer cells co-cultured with fibroblasts in vitro.Butein , a plant polyphenol, is a major biologically active component of the stems of We first measured the clonogenic growth of small numbers of the UACC-812 human breast cancer cell line co-cultured on monolayers of serum-activated, human fibroblasts in the presence of butein (2 μg/mL) or various other modulators of fibroblast function . In a subsequent experiment, we measured the dose-response effect on the clonogenic growth of UACC-812 breast cancer cells by pre-incubating the fibroblasts with varying concentrations of butein (10 μg/ml-1.25 μg/mL). Finally, we measured the clonogenic growth of primary breast cancer cells obtained from 5 clinical specimens with normal fibroblasts and with fibroblasts that had been pre-treated with a fixed dose of butein (2.5 μg/mL).Of the five modulators of fibroblast function that we tested, butein was by far the most potent inhibitor of clonogenic growth of UACC-812 breast cancer cells co-cultured with fibroblasts. Pre-treatment of fibroblasts with concentrations of butein as low as 2.5 μg/mL nearly abolished subsequent clonogenic growth of UACC-812 breast cancer cells co-cultured with the fibroblasts. A similar dose of butein had no effect on the clonogenic growth of breast cancer cells cultured in the absence of fibroblasts. Significantly, clonogenic growth of the primary breast cancer cells was also significantly reduced or abolished when the tumor cells were co-cultured with fibroblasts that had been pre-treated with a fixed dose of butein.We conclude that fibroblasts pre-treated with non-toxic doses of butein  no longer support the clonogenic growth of small numbers of primary breast cancer cells seeded into co-cultures. These results suggest that interference with the interaction between fibroblasts and breast cancer cells by the natural herbal compound, butein, should be further investigated as a novel experimental approach for possibly suppressing the growth of micrometastases of breast cancer. Rhus verniciflua Stokes. In Far Eastern countries such as Korea, Japan, and China, the compound has been traditionally used for treatment of pain, thrombotic disease, gastritis, stomach cancer, and parasitic infections [Butein  was passaged in Leibovitz's medium supplemented with 15% fetal calf serum. Normal fibroblasts (CCD-1068SK, ATCC) obtained from the breast of a 65 year old female were passaged at 37°C in minimal essential medium (Eagle's) supplemented with 2 mM L-glutamine, Earle's balanced salt solution (1.5 grams/Liter), sodium bicarbonate, 0.1 mM non-essential amino acids, 1 mL sodium pyruvate, and 10% fetal calf serum in a 5% COWe seeded 100 UACC-812 breast cancer cells into individual wells of a 96-well cell culture plate containing a confluent monolayer of fibroblasts growing in minimal essential growth medium supplemented as described above. At intervals of 3–4 days, fresh medium was added. After 14 days, the cells were fixed with 70% ethanol for 10 minutes prior to staining for 3 minutes with 0.1% toluidine blue. The wells were then washed with distilled water, and the numbers of colonies of tumor cells containing eight or more confluent cells were counted using inverted microscopy. Each experiment was performed in triplicate, and the means and standard deviations for each treatment and control group were then compared using a two-tailed, unpaired t-test.A monolayer of normal fibroblasts was seeded with 100 UACC-812 tumor cells/well containing complete culture medium (control) or medium supplemented with various modulators of fibroblast function. The fibroblast modulators that we tested included troglitazone . The tissues were carefully minced into small pieces and then digested overnight at 37°C in collagenase II  solution in cell culture medium. Epithelial cells and organoids were then isolated by differential centrifugation of the digest , washed,Co-culture of 100 UACC-812 human breast cancer cells on a monolayer of human fibroblasts without butein treatment typically yielded 50–75 distinct colonies of easily recognizable tumor cells on a background of fibroblasts  does not significantly reduce fibroblast viability [Clonogenic growth of small numbers of breast cancer cells in vivo ,6 as weliability  and is aiability ,2. MoreoRhus verniciflua Stokes are directly cytotoxic in vitro to human colon adenocarcinoma cells and lymphoma cells [Previous studies have shown that higher concentrations of butein extract from ma cells ,14. Butema cells . The mecma cells . Butein ma cells , tyrosinma cells , suppresma cells , inhibitma cells , and inhma cells .Our results suggest that butein may also suppress the growth of tumor cells through a second, indirect mechanism that does not involve direct toxicity to the tumor cells themselves. At this time, however, the precise molecular mechanisms by which butein interferes with the interaction between fibroblasts and breast cancer cells remain undefined.Clonogenic growth of small numbers of breast cancer cells co-cultured with fibroblasts pre-treated with butein is markedly reduced. These results suggest that butein can inhibit the growth of tumor cells through an indirect mechanism that interferes with the interaction between fibroblasts and breast cancer cells. Our results also suggest that the herbal compound butein should be further investigated as a potentially useful experimental approach for suppressing the growth of small numbers of breast cancer cells in early micrometastases.PPAR-peroxisome proliferation activator receptorCOX-cyclooxygenaseThe authors declare that they have no competing interests.MKS conceived and designed the study, performed the experiments with the primary tumor cells, analyzed the data from all experiments, and wrote this report. JT and GC performed the other experiments and reported the data.The pre-publication history for this paper can be accessed here:


A man in a suit and bowler hat walks awkwardly down the street, each convoluted step a labored movement. He lifts up one knee, then briefly stoops. Stepping forward, he swings the other leg out to the side then kicks high in the air. In this old Monty Python skit, the man works for the Ministry of Silly Walks. It's his job to walk this way. The rest of us, however, tend to stroll along—or throw baseballs, or lift coffee mugs—in a much more efficient manner.There's a nearly infinite number of silly walks, throws, and lifts, but somehow people tend to settle on one best way of doing these things. However, scientists studying motor control have been hard pressed to figure out what exactly we're doing when we move. People may be striking a balance between sloth and speed: too slow and our throws lack oomph; too fast, and instead of dunking our donuts in our coffee, we dunk our whole fist. Or people might be minimizing some version of jerk—physicists' and engineers' term for changes in acceleration.  But so far, such models that start by assuming people minimize error or jerk haven't allowed researchers to deduce what dictates how people move.To help solve this recalcitrant problem, Konrad Körding and colleagues, as reported in PLoS Biology, took a page from economists, who have long used equations called utility functions that incorporate the costs and benefits of a situation. Say you like oranges better than apples, but oranges cost more. Given a certain budget for fruit, the utility function says how many of each you should buy. Similarly, Körding and colleagues observed people's preferred movements, then inferred an underlying utility function that presumably describes bias in the nervous system for different movements.To see which movements people preferred, the researchers engaged people in a simple virtual reality system. The subjects moved a joystick that fought back: it was connected to a set of motors that produced varying forces—with a strong force for a short time, say, or a mild force for a longer time. Over and over, the subjects moved their cursors from one spot to another. After each pair of moves, the subjects then chose which of the two movements they found easier.In this way, the researchers were able to rank a large set of different movements relative to each other by individuals' preferences. They found a surprising amount of agreement among the subjects on which movements were preferable. They also got a counterintuitive result: as the duration of the resistance got longer, people actually preferred stronger resistance. The researchers speculate that subjects didn't mind larger resistance when it acted over a longer period because the force takes longer to ramp up to its maximum value. Subjects would have more time to adjust—just as when someone gradually pushes into you, you can stay standing by leaning into them, whereas if they shove you with the same force it can knock you off balance.By showing that utility functions can be of use not only in explaining the marketplace but also motor control, Körding and colleagues have added a new tool to biologists' repertoire. Though their approach hasn't closed the case on the mysteries of movement, it could help explain why we settle for a particular, non-silly walk.


Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference.Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart.Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples.The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit. Cluster sample study designs are a cost-effective way of sampling difficult to reach populations. Examples include sampling schools to obtain cluster samples of students or medical practitioners to sample patients. ClusterBoth the size of the intra-cluster correlation and the number of observations sampled within each cluster influence the power of the study. Even for a small intra-cluster correlation, as is often found in general practice and community samples, the loss of power can be appreciable, particularly if the size of the cluster is large,4.Estimates of the size of intra-cluster correlations come from post hoc examination of studies that have used either allocation or sampling by cluster and a number of intervention studies have published observed intra-cluster correlation coefficients -6. Many Intra-cluster correlation varies within a study and depends on the outcome under analysis,4,6. TheIn one Australian study Carlin and Hocking examinedThis paper reports some of the intra-cluster correlations observed in the Bettering the Evaluation and Care of Health (BEACH) program, a large cross-sectional survey of general practice patient encounters in Australia, where a random sample of general practitioners was used as the primary sampling unit.The BEACH study draws a new random sample of Australian general practitioners (GPs) each year, and this provided an opportunity to assess the stability of intra-cluster correlation coefficients across successive samples. If a population is re-sampled using the same cluster survey design, will the intra-cluster correlation coefficient for a particular outcome be the same across samples? This analysis takes an applied approach, examining the observed intra-cluster correlations for a range of demographic, morbidity and treatment outcomes.The BEACH program is a continuous study of general practice activity commenced in 1998. The BEACH method is described in detail elsewhere and a brief summary is reported below.A random sample of approximately 1,000 general practitioners (GPs) is drawn each year from the Health Insurance Commission's sampling frame of the population of GPs in Australia. The GP population is randomly ordered into a list and GPs are recruited sequentially from the list, with re-randomisation of the sampling frame every three years,12. GPs A single page encounter form contains elements including:• Patient age and sex.• Whether English was the main language spoken at home.• Whether the patient holds an Australian health care concession card.• The problems managed by the GP at the encounter (up to four problems per encounter).• Treatments received at the encounter, including medications, other procedures, referrals and orders for pathology and imaging tests.Although sample weights are calculated each year for population estimates, the outDescriptive outcomes were defined as rates, means and percentages of single variables, e.g. mean age, per cent of encounters with female patients, per cent of encounters where at least one respiratory problem was managed. BEACH samples the GP-patient encounter, not independent patients. If a patient returns to the GP in the sampling period then that patient contributes two (or more) encounters to the sample. Therefore BEACH estimates are not true "prevalence" rates because the denominator, the population of GP-patient encounters, is many times larger than the population of all general practice patients. To avoid misunderstanding in this paper we have used the term "descriptive" rather than "prevalence" to report single variable estimates and their accompanying intra-cluster correlation coefficients. Descriptive rates are interpreted for example as "Proportion of patients at encounter who are female".Demographic variables include patient sex, patient age, whether the patient held a health care concession card and whether the main language spoken at home was not English.Problems were classified using the International Classification of Primary Care (ICPC-2). The uppTreatment outcomes included the proportion of encounters that resulted in at least one medication, the proportion that received at least one referral, the proportion that received at least one order for an imaging test and the proportion receiving at least one order for a pathology test.Intra-cluster correlation coefficients were calculated for associations between variables using logistic regression e.g.: the effect of patient age (predictor) on the rate of cardiovascular problems (outcome).Obtaining the sample size for cluster designs involves calculating the sample size under the assumption of simple random sampling and then inflating the number of observations to allow for the design effect of the cluster sample. The design effect (Deff) of an outcome has been defined as the ratio of the variance taking into account the cluster sample design and the variance of a simple random sample (srs) design with the same number of observations.(clustersample)/Variance(srs)Deff = VarianceIntra-cluster correlations and their standard errors for the outcome variables were calculated using the method described by Carlin & Hocking. SpecifiThe intra-cluster correlation coefficient (ICC) was then calculated from the design effect using the formula:ICC = (Deff - 1)/(k - 1)and the approximate standard error (SE) of the intra-cluster correlation was calculated using the formula,6:m = number of clusters, k = mean number of observations per cluster.where The intra-cluster correlations and respective 95% confidence intervals for the second BEACH year sample from the period April 1999 to March 2000 were compared against those in the year 5 sample (April 2002 to March 2003) to assess whether the intra-cluster correlations were consistent across samples over time. All calculations specified the GP as the primary sampling unit.From April 1999 to March 2000, 1,047 GPs were recruited, recording a sample of 104,700 patient encounters. From April 2002 to March 2003, 1,008 GPs were recruited and 100,800 encounters recorded. Table The two samples of patient encounters were similar in terms of demographics Table  In the yFor descriptive estimates of demographic variables the intra-cluster correlation ranged from 0.055 for sex of patient at encounter to 0.451 for language spoken by the patient at home. Table . With a For descriptive estimates of the management rates of morbidity problems, the intra-cluster correlations ranged from 0.005 for estimates of eye problems to 0.059 for estimates of psychological problems, with design effects of between 1.5 and 6.8 respectively.The intra-cluster correlation coefficients for treatments received ranged from 0.028 for any imaging tests ordered to 0.056 for any medications.For bivariate relationships between an outcome and predictor, the association ICCs were considerably smaller than the descriptive ICCs Table . This paWhen analysing the association between cardiovascular problems as the outcome and selected demographic variables, the ICCs ranged from 0.042 (patient language as the predictor) to 0.003 (patient sex as the predictor) declare that they have no competing interests.SK conceived the research questions, undertook the analysis and wrote the main draft of the manuscript. PC participated in formulating the research questions and the design of the analysis, undertook a literature search and assisted in the writing of the main draft and subsequent revisions of the manuscript.The pre-publication history for this paper can be accessed here:


The SARS coronavirus is the etiologic agent for the epidemic of the Severe Acute Respiratory Syndrome. The recent emergence of this new pathogen, the careful tracing of its transmission patterns, and the ability to propagate in culture allows the exploration of the mutational dynamics of the SARS-CoV in human populations.We sequenced complete SARS-CoV genomes taken from primary human tissues (SIN3408, SIN3725V, SIN3765V), cultured isolates (SIN848, SIN846, SIN842, SIN845, SIN847, SIN849, SIN850, SIN852, SIN3408L), and five consecutive Vero cell passages (SIN2774_P1, SIN2774_P2, SIN2774_P3, SIN2774_P4, SIN2774_P5) arising from SIN2774 isolate. These represented individual patient samples, serial in vitro passages in cell culture, and paired human and cell culture isolates. Employing a refined mutation filtering scheme and constant mutation rate model, the mutation rates were estimated and the possible date of emergence was calculated. Phylogenetic analysis was used to uncover molecular relationships between the isolates.th October 2003, including 22 from patients in Singapore, revealed the mutations engendered during human-to-Vero and Vero-to-human transmission as well as in multiple Vero cell passages in order to refine our analysis of human-to-human transmission. Though co-infection by different quasipecies in individual tissue samples is observed, the in vitro mutation rate of the SARS-CoV in Vero cell passage is negligible. The in vivo mutation rate, however, is consistent with estimates of other RNA viruses at approximately 5.7 × 10-6 nucleotide substitutions per site per day (0.17 mutations per genome per day), or two mutations per human passage (adjusted R-square = 0.4014). Using the immediate Hotel M contact isolates as roots, we observed that the SARS epidemic has generated four major genetic groups that are geographically associated: two Singapore isolates, one Taiwan isolate, and one North China isolate which appears most closely related to the putative SARS-CoV isolated from a palm civet. Non-synonymous mutations are centered in non-essential ORFs especially in structural and antigenic genes such as the S and M proteins, but these mutations did not distinguish the geographical groupings. However, no non-synonymous mutations were found in the 3CLpro and the polymerase genes.Close examination of whole genome sequence of 54 SARS-CoV isolates identified before 14Our results show that the SARS-CoV is well adapted to growth in culture and did not appear to undergo specific selection in human populations. We further assessed that the putative origin of the SARS epidemic was in late October 2002 which is consistent with a recent estimate using cases from China. The greater sequence divergence in the structural and antigenic proteins and consistent deletions in the 3' – most portion of the viral genome suggest that certain selection pressures are interacting with the functional nature of these validated and putative ORFs. The Severe Acute Respiratory Syndrome (SARS) was first reported in November 2002 and rapidly spread to a number of distant global regions by early 2003. A new coronavirus, the SARS-CoV, was identified to be the cause of SARS ,2 and waPreviously, our analysis of 14 SARS sequences (five of which originated from Singapore) in May 2003 indicated that there are two different genotypes circulating in the world . Recentl). The RNA genome templates were converted into double strand cDNA and sequenced as previously described [).SARS-CoV from the primary patient tissues were isolated by homogenizing the tissues in PBS buffer followed by a low speed centrifugation to obtain the viral particle containing supernatant. The virus-containing samples were also inoculated into Vero cell E6. The cells were maintained at 37°C using the usual viral cell culture media, and repassaged after 7 days of incubation. The virus-containing supernatants of homogenize or different passages of Vero cell E6 showing CPE were centrifuged at 23,000 RCF for 2.5 hours to pellet the viral particles and followed by RNA extraction using the QiAmp viral RNA mini kit (Qiagen, A number of single nucleotide variations (SNVs) were further confirmed using a sensitive Mass Spectrometry based genotyping assay that was developed within our institute . The RNAWe aligned the 54 SARS-CoV genomes using CLUSTALW . To miniq be the rate of noisy mutation in a genome (based on our findings, as reported earlier in the text, we conservatively set , i.e. about two per SARS-CoV genome). The probability that, at a given nucleotide, a noisy mutation is shared by exactly i out of m different isolates is . Thus, the probability that a given nucleotide position has an erroneous mutation shared by more than k isolates is . In a genome with n bases, applying the Bonferroni inequalities, the probability that at least one position is corrupted by noise more than k times is p(k,n,m) ≤ n × s(k,m). In the case of 54 SARS-CoV genomes analyzed in this paper, , m = 54, k = 2, n = 30000, and hence the p-value of mutations that satisfy the filter is ≤ 2.2 × 10-4.The significance of the variations that pass the proposed mutation filter  can be assessed by calculating the probability that a random noise would meet the filtering criterion. The null hypothesis is that the noisy variations are generated independently between genomes. Let d found in an isolate from its ancestor is proportional to the mutation rate k and the temporal difference t between the isolate and its ancestor, so that d = k × t. Based on the Singapore patients contact tracing information  and the time difference (t) for each pair, and estimate the mutation rate k for the model using least square fitting. The goodness-of-fit were measured using the adjusted R-square statistics.In the estimation of SARS-CoV daily mutation rate, we employed the conservative constant mutation rate model , where tdx = d0 + kx, where k is the daily rate of mutation, x is the sampling date measured relative to 1st November 2002, and dx is the number of mutations, as compared to the civet cat isolate, of the isolate sampled at date x. Twelve data points were calculated and used to fit the model. The date of origin can be solved by solving x for dx = 0. The goodness-of-fit was measured using the adjusted R-square statistic.Another pertinent question in the analysis of SARS-CoV evolution is prediction of the possible date of origin of the human SARS-CoV. Based on the animal-origin hypothesis of SARS-CoV, we assumed the SARS-CoV isolated from palm civet cat as the putative principal isolate that infected the human population. Adhering to the constant mutation rate model, we fit the following model: in vitro cell culture are negligible.First, we sought to determine the rate of mutation of the SARS-CoV in Vero cell culture. To achieve this, we subjected SIN2774 isolate to 5 passages in Vero cells. At the appearance of cytolysis at each passage samples were withdrawn and their genomes completely sequenced. Any ambiguities by capillary sequencing were clarified by mass spectroscopic validation . Our resNext, we asked whether the transition from human tissue to growth in Vero cell culture engendered either mutations or clonal selection. The SARS-CoV were sequenced from three human tissue-Vero cell culture pairs of viral samples from Singapore and one pair was obtained from the public domain . The results shown in Table Singapore encountered an unusual incident where a stable lab SARS-CoV isolate commonly used for in vitro experimentation accidentally infected a laboratory worker . We sequ-5, or 2.25 errors per SARS-CoV genome. Accordingly, we suspected that sequencing errors in the reported SARS sequences would be approximately 1–2 bases per reported genome. We used this information to assess the true sequence variants reported in the public SARS sequence databases employing a "mutation filter" [p ≤ 2.2e - 4) as compared to the probability of finding a false mutation shared by more than one isolate (p ≤ 0.19). These results are consistent with our error estimates as outlined above.Inferring phylogenetic relationships between the known SARS-CoV isolates using existing public data has been problematic because of the potential for sequencing errors. Moreover, the rate of SARS-CoV mutation in culture was not previously known and was thought to be significant given the mutation rates in other RNA viruses. Our experiments provided information as to the potential causes and rates of sequence variations of the SARS-CoV in culture. Based on our Vero cells passages and human-to-Vero transition data, we estimated that, at most, one sequence variation from the original tissue virus can be accounted for by in vitro culture artifacts. The average base-calling error probability (as reported by PHREP ) of our We tested the biological validity of this approach by examining the mutational frequency of known genes in the SARS genome. Because of the importance of the 3CL protease and the polymerase for viral replication, we suspected that true non-synonymous mutations in the SARS-CoV present in clinical samples might be rare in these two ORFs in comparison to other structural genes such as those encoding the S, M, and N proteins. Without a mutation filter, sequence variations are commonly observed in the 3CL protease and the polymerase genes. However, when mutations are identified only as variants seen in two or more isolates, then no mutations are detected in the critical 3CL protease and polymerase genes, whereas mutations are noted in the S, M, and N genes regardless of the filter stringency Figure . TherefoUsing this filter stringency, we assessed the phylogenetic relationship between all 54 isolates describing the recent SARS epidemic. TOR2, Urbani, SIN2500, HKU-39849, CUHK-Su10 formed the core of the early isolates. Employing these as "root", four major clusters appeared: two Singaporean branches, one Taiwan branch, and one North China branch . The rates for synonymous and non-synonymous mutations were equivalent at 2.5 × 10-6 and 3.2 × 10-6 nucleotide substitutions per site per day respectively. Using the Singapore isolates with known date of onset, and using the SZ3 and SZ16 genomes isolated from palm civet cat [-6 nucleotide substitutions per site per day, (adjusted R-square = 0.5880) and the estimated possible "date" of SZ3/SZ16 emergence was Oct 21, 2002. Overall, the mutation rate of SARS-CoV appears to be consistent with the reported rate of other viruses [We obtained the precise dates of symptom onset of 13 Singaporean cases (Table S1). Using the common mutations identified through application of the mutation filter, we employed the constant mutation rate model and estimated the mutation rate of the SARS-CoV during this recent epidemic. We estimated the mutation rate to be 0.1722 nucleotides per day, or 5.7 × 10ivet cat  as the pThe mutational analysis also revealed 5 separate deletions and one insertion that distinguished the different isolates , cases reported in North China, and cases found in Taiwan. Moreover, we show that these molecular sequence associations can be effectively used to more precisely reconstruct contact tracing. Our estimated the daily substitution rate of SARS-CoV to be 0.1722 nucleotides, or 5.7 × 10 viruses ,14. Taki[et. al. , examininsortium , examininsortium  projecteNone declared.VBV and ETL performed most of the data analysis and prepared the draft manuscript. STSY and LAE provided SARS-CoV samples from patients and Vero cells. KFT and OEE provided continue SARS-CoV containing Vero cell passage samples. YR and LWS designed the experiments and coordinated sample acquiring and the viral genome sequencing. CLW and TZ generated all DNA sequence data. WHL processed all DNA sequence and assembled the viral genomes. JL verified all sequence variations by conducting MALDI-TOF mass spectrometry analysis. PK assessed the effects of nucleotide variations to ORFs and their proteins. VBV and PML carried out the mathematical and statistical analysis.The pre-publication history for this paper can be accessed here:Table S1 List of the sequences used in the analysis. This list is available at http://giscompute.gis.a-star.edu.sg/sars_mut_dyn/Click here for fileTable S2 Single nucleotide variations (SNVs) detected initially in capillary sequencing (second row) and subsequently confirmed by MALDI-TOF MS-based genotyping (first row). This table is available at http://giscompute.gis.a-star.edu.sg/sars_mut_dyn/Click here for fileTable S3 Complete list of single nucleotide variations (SNVs) observed in the 54 SARS-CoV isolates. The Singapore sequences used were all based on capillary sequencing. This data is available at http://giscompute.gis.a-star.edu.sg/sars_mut_dyn/Click here for file


Recently, a global commitment has been made to expand access to antiretrovirals (ARVs) in the developing world. However, in many resource-constrained countries the number of individuals infected with HIV in need of treatment will far exceed the supply of ARVs, and only a limited number of health-care facilities (HCFs) will be available for ARV distribution. Deciding how to allocate the limited supply of ARVs among HCFs will be extremely difficult. Resource allocation decisions can be made on the basis of many epidemiological, ethical, or preferential treatment priority criteria.Here we use operations research techniques, and we show how to determine the optimal strategy for allocating ARVs among HCFs in order to satisfy the equitable criterion that each individual infected with HIV has an equal chance of receiving ARVs. We present a novel spatial mathematical model that includes heterogeneity in treatment accessibility. We show how to use our theoretical framework, in conjunction with an equity objective function, to determine an optimal equitable allocation strategy (OEAS) for ARVs in resource-constrained regions. Our equity objective function enables us to apply the egalitarian principle of equity with respect to access to health care. We use data from the detailed ARV rollout plan designed by the government of South Africa to determine an OEAS for the province of KwaZulu–Natal. We determine the OEAS for KwaZulu–Natal, and we then compare this OEAS with two other ARV allocation strategies: (i) allocating ARVs only to Durban  and (ii) allocating ARVs equally to all available HCFs. In addition, we compare the OEAS to the current allocation plan of the South African government . We show that our OEAS significantly improves equity in treatment accessibility in comparison with these three ARV allocation strategies. We also quantify how the size of the catchment region surrounding each HCF, and the number of HCFs utilized for ARV distribution, alters the OEAS and the probability of achieving equity in treatment accessibility. We calculate that in order to achieve the greatest degree of treatment equity for individuals with HIV in KwaZulu–Natal, the ARVs should be allocated to 54 HCFs and each HCF should serve a catchment region of 40 to 60 km.Our OEAS would substantially improve equality in treatment accessibility in comparison with other allocation strategies. Furthermore, our OEAS is extremely different from the currently planned strategy. We suggest that our novel methodology be used to design optimal ARV allocation strategies for resource-constrained countries. A mathematical model that allows to determine a strategy for distribution of limited medical resources  such that each individual in need will have an equal chance of receiving treatment The HIV/AIDS epidemic is having a devastating impact in sub-Saharan Africa and other resource-constrained regions. Recently, the World Health Organization and other organizations have committed to expand access to antiretrovirals (ARVs) in the developing world, the United States government has pledged to provide $15 billion for AIDS in Africa and the Carribean, and drug prices have fallen . It has Here, we use operations research to address this important resource allocation problem and to design ARV allocation strategies that are rational and equitable. The allocation decisions that we make here are based on ethical criteria, and not on epidemiological or preferential treatment priority criteria. Specifically, we determine the optimal allocation strategy that would ensure that each individual with HIV has an equal chance of receiving ARVs. We present a novel spatial mathematical model of treatment accessibility that we use in conjunction with an equity objective function to determine an optimal equitable allocation strategy (OEAS) for ARVs in a resource-constrained region. We quantify how changing the size of the catchment region surrounding each HCF, and the number of HCFs utilized for ARV distribution, alters the OEAS. Specifically, we use data from the detailed ARV rollout plan designed by the government of South Africa to determine an OEAS (based upon a variety of assumptions) for the province of KwaZulu–Natal. We also discuss how our proposed ARV allocation strategy differs from the currently proposed plan.Our current analysis is applied to the South African province of KwaZulu–Natal, although our methodology could be applied to any resource-constrained setting. KwaZulu–Natal is the largest province in South Africa with a population of approximately 9.4 million and has more people infected with HIV than any other province  as a weighting function that determines the treatment accessibility to a HCF based upon distance i,j,d and iI as the number of people with HIV in community i. The distance, ij,d between community i and HCF j is based on the longitude (lon) and latitude (lat) of each location and is determined byWe assume that the number of people with HIV who will travel to a specific HCF is directly proportional to the number of individuals with HIV in that particular community, but that the probability of an individual traveling to receive ARVs (i.e., the treatment accessibility) decreases with distance from the HCF. We define R is the radius of the earth, taken to be 6,371 km, and the angles are in radian measure. We calculate the “effective demand” of community i on HCF j to be the number of people with HIV in community i that will travel to HCF j for ARV regimes, namely, f(i,jd)iI. Thus, demand on HCFs for ARVs is reduced by the treatment accessibility function. Our model is conceptually similar to the “gravity” models that have been used to predict retail travel [f(d) = exp(−kd2), where k is a dispersal length scale parameter determining the radius of the catchment region. The size of the actual catchment regions is unknown, but based upon distances from communities to HCFs in KwaZulu–Natal (see k = 0.003786). We vary the catchment region by considering a 20-km radius (k = 0.0151) and a 60-km radius (k = 0.00168). The different catchment regions that we simulate (with radii of 20 km, 40 km, and 60 km) for each HCF are illustrated in where l travel , plan lal travel , and detl travel . Howeveratal see A we assu= exp−kd, where kj,j, D to beTo determine how many ARVs should be allocated to each HCF, we first calculate how a given supply of ARVs will be distributed from each HCF to the surrounding communities in the catchment region. We calculate the “effective demand” on HCF j (where there are m communities). Then, we model the distribution of ARVs from a HCF to each community within the catchment region as the proportion of the “effective demand” on HCF j that is contributed by the respective community. Accordingly, ARVs will be distributed from HCF, j, to each community as the ratiowhich sums the “effective demand” of all communities on HCF i by the drug supply allocated to HCF j isTherefore, the number of people treated in community jS is the number of regimes allocated to HCF j. Hence, the total number of people with HIV treated in community i,i,T summing over all n HCFs iswhere A ARV regimes for a total of We establish an equity objective function to determine the optimal equitable allocation of ARVs to each HCF so that all individuals with HIV have an equal chance of receiving treatment. To obtain the same fraction of treated individuals in each community, given that there are E, by solving for the number of ARVs to be allocated to each HCF (S1, S2,…, Sn), whilst enforcing the following three constraints: (i) ensure that the total number of ARVs available is equal to the sum of the supply allocated to all HCFs,Our goal is to minimize jS ≥ 0, j = 1…n); and (iii) ensure that the number of people treated in each community is not greater than the number of people with HIV in the community (iT ≤ i, iI = 1…m). We note that if a different objective is required, then all of our preceding analysis still holds and only the functional form of the objective function needs to be altered. To solve the problem, and determine the OEAS, we used successive linear programming operations research techniques [(ii) ensure that only a positive number of ARVs are allocated to each HCF (chniques .k = 0.003786). The proportion of infected individuals that are treated at each location is displayed graphically in E = 0.27 for our OEAS, compared with (i) E = 0.50 and (ii) E = 133.88 for the comparison allocation strategies. There is large diversity in the fraction of individuals with HIV treated per community when equal quantities of ARVs are given to each HCF, evidenced by an inter-quartile range of 0.025%–41.746% compared with inter-quartile ranges of 0%–0% and 0.011%–9.982% for the first comparison strategy and our OEAS, respectively. Therefore, equal access is not obtained if equal quantities of ARVs are allocated to each HCF. Obviously, allocating to only one HCF (the first comparison strategy) could also be considered unequal because although the inter-quartile range is minimal, effectively only one community (Durban) receives ARVs. Our OEAS, while not perfect, achieves the best equality possible given the accessibility constraints and limited ARV supply.The OEAS of ARVs in KwaZulu–Natal that we determined is complex see A and 3B.The catchment region for HCFs is a factor of large uncertainty. We considered three catchment region sizes: radii of 20 km, 40 km, and 60 km. We also simulated two additional cases with increased numbers and locations of HCFs  should be used. The strategy that we are advising may be fairly easy to accomplish at the policy level because the health-care infrastructure  already exists, although consideration must be made for issues such as the training and transportation that is necessary, which may be costly. In contrast, increasing the size of catchment regions may be very difficult. Obviously, increasing both the number of HCFs and the size of the catchment region each services would substantially increase equality of access to health care in KwaZulu–Natal.Future modeling studies could extend our work by not making the simplifying assumption that all patients have similar ease of travel over the same distance and by including weighting functions on distance impedance for different communities  (D. P. Wilson, J. O. Kahn, S. M. Blower, unpublished data). Here, we have shown how to calculate optimal ARV allocation strategies based upon the principle of equity. Future research is necessary to compare ARV allocation strategies based upon the principle of efficiency  in order to determine whether utilizing different principles for optimization would result in similar (or different) allocation strategies.The World Health Organization and the Joint United Nations Programme on HIV/AIDS have identified three core principles that should underlie the effort to fairly distribute ARVs, namely: urgency, equity, and sustainability . They stAlthough we have focused on one equitable strategy, there are many other ARV allocation strategies that are ethical. Uneven access to HIV treatment has the very real potential to fracture social and political structures and could lead to intrastate and/or interstate conflict . GovernmTreatment priority decisions for individuals could be based on many different criteria, including disease progression , socioeconomic status, ethnicity, and who is thought to have the greatest risk of transmitting infections . Although it could be argued that behavioral core groups should be targeted to receive ARVs because this may have the greatest epidemiological impact, such an allocation strategy would be neither feasible nor practical to implement. For example, sex workers are an obvious behavioral core group, but many women would likely claim to be sex workers if they knew that ARVs were only available to sex workers. Additionally, the ethics of targeting such groups in favor of other societal groups must be questioned. It could also be argued that, to maximize the preventative effect of ARV therapy, ARVs should be concentrated in virological core groups  ,26; thisOur model has been applied to the South African province of KwaZulu–Natal, but it can be applied by government health officials in any resource-constrained country. In many of the countries worst affected by the HIV pandemic, scarcity of resources will mean that not everyone that could potentially benefit from ARVs will be able to access them. Many of the decisions that must be made to develop an effective response to the HIV/AIDS epidemic are inevitably underpinned by ethical considerations. Leadership in most resource-constrained regions cannot avoid these decisions. Whilst there has been considerable attention given to South Africa, many other countries worldwide either have plans in place (e.g., Brazil, Thailand, and Botswana) or are in the process of developing national programs for ARV distribution through the public health system  . LegitimAntiretroviral drugs can change the lives of patients with HIV/AIDS. Their high price, however, means that many poor countries do not have enough of these drugs to treat all the people who need them. The decision of who will get treatment is very difficult, and different ways to come up with ethical solutions to the problem have been proposed.One of the approaches is to try to make sure that every infected person has the same chance to get antiretroviral drugs. David Wilson and Sally Blower, the authors of this study, wanted to find a scientific strategy to achieve this goal of equal access.They used mathematical models to calculate how to distribute available drugs among hospitals and doctor's offices so that each patient in a particular area had an equal chance to get treated.When they used their approach on a real example, the South African province of KwaZulu–Natal, they found that making some changes to the current plans for drug distribution would lead to more equal access among all of the individuals with HIV in the province. Instead of only 17 out of the 54 health care facilities in KwaZulu–Natal distributing the drugs (which is the current plan of the South African government), Wilson and Blower calculate that it would be fairer if all 54 facilities distributed the medicines.Mathematical models like the one used here are always based on assumptions and simplifications. As a consequence, they are never perfect matches for a real-life situation, but they can help to guide complicated decisions. This article suggests that the approach Wilson and Blower developed could help to determine strategies for equitable allocation of limited HIV treatment resources.The authors hope that the tools they developed will be used by policy makers in resource-poor countries to guide their strategies. They are keen to work with these policy makers to adapt and optimize the method to local settings and priorities.http://www.who.int/hiv/pub/advocacy/en/ethicsmeetingreport_e.pdfReport by the World Health Organization and the Joint United Nations Programme on HIV/AIDS on ethics and equitable access to HIV/AIDS treatment: http://www.who.int/ethics/en/background-macklin.pdfRuth Macklin's report on ethics and equity in access to HIV treatment: http://www.who.int/ethics/en/background-pro-poor3.pdfThe Pro-Poor Health Policy Team's report on priority in HIV/AIDS treatment: http://www.who.int/bulletin/volumes/82/1/en/news.pdfNews article from the World Health Organization Bulletin on the South African HIV/AIDS treatment program: