The ideal conservation planning approach would enable decision-makers to use population viability analysis to assess the effects of management strategies and threats on all species at the landscape level. However, the lack of high-quality data derived from long-term studies, and uncertainty in model parameters and/or structure, often limit the use of population models to only a few species of conservation concern. We used spatially explicit metapopulation models in conjunction with multi-criteria decision analysis to assess how species-specific threats and management interventions would affect the persistence of African wild dog, black rhino, cheetah, elephant, leopard and lion, under six reserve scenarios, thereby providing the basis for deciding on a best course of conservation action in the South African province of KwaZulu-Natal, which forms the central component of the Maputaland-Pondoland-Albany biodiversity hotspot. Overall, the results suggest that current strategies of managing populations within individual, small, fenced reserves are unlikely to enhance metapopulation persistence should catastrophic events affect populations in the future. Creating larger and better-connected protected areas would ensure that threats can be better mitigated in the future for both African wild dog and leopard, which can disperse naturally, and black rhino, cheetah, elephant, and lion, which are constrained by electric fences but can be managed using translocation. The importance of both size and connectivity should inform endangered megafauna conservation and management, especially in the context of restoration efforts in increasingly human-dominated landscapes. Conserving biodiversity with limited budgets requires allocating resources to actions that provide the highest return on investment The concept of population viability is pivotal to conservation planning and decision-making A decision analysis framework in combination with population viability analysis is considered one of the best ways to measure the effects of conservation actions on multiple species and account for uncertainty in population viability analysis th century they had declined dramatically or were driven to local extinction through over-hunting and persecution by humans Ceratotherium simum simum) population increased from less than 20 individuals in the iMfolozi area in 1895 to more than 17,000 in the wild today Diceros bicornis minor) Range Expansion Project Lycaon pictus) KwaZulu-Natal metapopulation management program Acynonix jubatus), elephant (Loxodonta africana) and lion (Panthera leo) The Maputaland-Pondoland-Albany biodiversity hotspot is internationally recognized for its high levels of species richness and endemism, which are under different levels of threat Panthera pardus) and lion in the South African province of KwaZulu-Natal, which forms the central component of the Maputaland-Pondoland-Albany hotspot. The six study species are all listed under the IUCN Red List In this study, we used multi-criteria decision analysis in combination with spatially explicit metapopulation models to create a rank order for six different reserve scenarios in order to decide which conservation action would best enhance the persistence of African wild dog, black rhinoceros, cheetah, elephant, leopard  and then compared this return to 26 alternative land uses in the area so that we were able to select only areas where conservation land use is more profitable. Full details are provided in A flow chart summarizing the modelling and decision analysis framework is provided in r <0.60), which could be expected We derived the habitat suitability map from species distribution models developed using MaxEnt The non-climatic factors were represented by thirteen habitat and four human impact variables. The habitat variables representing the environmental variability of the area were aspect, digital elevation model (DEM), geology, slope and soil type. The slope and aspect grids were derived from DEM Species distribution models were then evaluated using the area under the curve (AUC) of the Receiver Operating Characteristic (ROC) curve. MaxEnt was run under the “auto-features” mode Biggest Reserve scenario, the metapopulation structure of each species was recognized by clustering together suitable cells if they were below a certain neighbourhood distance based on average home range size for each species Small Reserve scenario, individual, fenced, protected areas were considered populations. Under the Big Reserve scenario, the spatial metapopulation structures were obtained in ArcEditor 9.2 Biggest Reserve scenario suitable habitat currently protected, using a spatial layer where only adjacent protected areas were merged together. Under the Small and Big Connected Reserve scenario, we aggregated the most-connected big patches identified under the Big Reserve scenarios with the closest (but not directly adjacent) reserves identified under the Small Reserve scenarios. Under the Big and Connected Reserve scenario, the spatial metapopulation structures were obtained in ArcEditor 9.2 Small and Big Connected Reserve scenarios via designated linkages. Under the Bigger and Connected, but Cheap, Reserve scenario, we added to the patches identified under the Big and Connected Reserve scenarios suitable habitat whereby conservation land use was more profitable than alternative land uses We selected the metapopulation structure for each species based on habitat suitability thresholds and the neighbourhood distance. For all species, the suitability threshold in MaxEnt was selected based on a balance between maximizing sensitivity and minimizing predicted area Reserve scenarios. A friction surface, where each grid cell value represents the relative cost of dispersing through that cell, was used to recognize potential dispersal corridors from one population to another The permeability of the background matrix to dispersal between different populations was modelled for African wild dog and leopard only using a cost surface approach. Permeability was modelled for African wild dog and leopard only because, to prevent conflict with local communities and private landowners from occurring, all other species would continue being managed artificially within electrified fences under all To model metapopulation dynamics, we developed an age structured matrix model with annual time steps for each recognized population. Males and females were included as separate matrices for all species, but had the same age structures. K) for each modelled population was estimated by using different methods for carnivores and herbivores respectively. For elephant and black rhino, K was calculated by dividing the spatial extent of each population by its population density estimate. Specifically, we classified suitable habitat into low, medium and high suitability areas for both species. We then used a population density estimate based on forage/browse availability for each class , indicating they were ‘highly accurate’ Small to the Biggest Reserve scenarios , whilst African wild dog, cheetah and lion are at considerable risk of extinction (>25%)  . However disease . ParticuBig Reserve scenarios the probability of extinction decreased for all species, but remained high for cheetah under the basic, threat and threat mitigation scenarios (>22%), as well as black rhino, elephant and leopard under increased severity of poaching in the future (>29%). The probability of extinction decreased for all species under both the Small and Big Connected Reserve scenarios and the Big and Connected Reserve scenarios, but was higher for the former. While under the Small & Big Connected Reserve scenario African wild dog, cheetah and leopard remained at high risk of extinction, under the Big and Connected Reserve scenarios only the leopard metapopulation would still be at high risk of extinction under the increased poaching scenarios   under high levels of poaching for skins   . The proer year) . Under tAccording to the sensitivity analyses, increasing carrying capacity was the most important factor decreasing the probability of extinction for African wild dog, cheetah and lion, whilst increased severity of poaching was the most important factor increasing the metapopulation probability of extinction for black rhino, elephant and leopard . ChangesBigger and Connected, but Cheap, Reserve scenarios were the most effective in reducing the metapopulation probability of extinction for all species, whilst the Small Reserve scenarios were the least effective  In the short term, the first step to create larger and better connected protected areas would be to drop internal fences between neighbouring reserves to create larger conservancies and use smaller reserves to enhance connectivity among larger patches (Big & Connected Reserve scenario). This will be particularly beneficial for the carnivore species, which are currently heavily managed with little hope to address urgent conservation issues of the species Bigger and Connected, but Cheap, Reserve scenario) will be the most effective strategy to decrease extinction risk and stabilize numbers of all species. This is particularly so for African wild dog, cheetah, and lion. However, increased levels of poaching for animal parts could still be very detrimental for leopard, black rhino and elephant even under the Bigger and Connected, but Cheap, Reserve scenario. Mitigating these threats in the future, by reducing the demand, may require developing innovative and at the same time controversial initiatives, such as legalizing the trade in rhino horn and ivory The second step, instead, will require merging the most-connected large and small patches by using already identified linkages Establishing such a protected area network requires long-term political, social and financial commitments that go far beyond simply declaring new parks Bigger and Connected, but Cheap, Reserve scenario), it would require capital investments worth more than 2200 USD km−2 and management costs in the range of 500 to 4500 USD km−2 yr−1 to make operations sustainable Acquiring land for protected area expansion is not an option in the study area because of both limited financial resources and unwillingness to sell of both local communities and private landowners In conclusion, using population viability analysis in combination with decision-analysis, as an alternative to traditional conservation planning, can help deal with species-specific needs for the amount and spatial configuration of protected areas. Our results suggest that having a network of larger protected areas connected either through dispersal or translocation, where fences prevent conflict with humans from occurring, may represent the most effective way to mitigate threats and maintain viable metapopulations of wide-ranging species in human-dominated landscapes. Particularly, as technologies for the translocation of such species are well-verified Appendix S1Supplementary Methods and Results.(DOCX)Click here for additional data file.


Treatment of psychotic disorders consists primarily of second generation antipsychotics, which are associated with metabolic side effects such as overweight/obesity, diabetes, and dyslipidemia. Evidence-based clinical practice guidelines recommend timely assessment and management of these conditions; however, research studies show deficits and delays in metabolic monitoring and management for these patients. This protocol article describes the project ‘Monitoring and Management for Metabolic Side Effects of Antipsychotics,’ which is testing an approach to implement recommendations for these practices.This project employs a cluster randomized clinical trial design to test effectiveness of an evidence-based quality improvement plus facilitation intervention. Eligible study sites were VA Medical Centers with ≥300 patients started on a new antipsychotic prescription in a six-month period. A total of 12 sites, matched in pairs based on scores on an organizational practice survey, were then randomized within pairs to intervention or control conditions.Study participants include VA employees involved in metabolic monitoring and management of patients treated with antipsychotics at participating sites. The intervention involves researchers partnering with clinical stakeholders to facilitate tailoring of local implementation strategies to address barriers to metabolic side-effect monitoring and management. The intervention includes a Design Phase ; Implementation Phase ; and a Sustainability Phase. Evaluation includes developmental, implementation-focused, progress-focused and interpretative formative evaluation components, as well as summative evaluation. Evaluation methods include surveys, qualitative data collection from provider participants, and quantitative data analysis of data for all patients prescribed a new antipsychotic medication at a study site who are due for monitoring or management of metabolic side effects during the study phases. Changes in rates of recommended monitoring and management actions at intervention and control sites will be compared using time series analyses.Improving monitoring for metabolic side effects of antipsychotics, as well as promoting timely evidence-based management when these effects emerge, will lead to improved patient safety and long-term outcomes. This article discusses key strengths and challenges of the study.NCT01875861 Department of Veterans Affairs (VA) and elsewhere. For example, while 3.4% of VA service users have a diagnosis of schizophrenia, patients with this serious mental illness (SMI) account for 11.7% of VA healthcare costs [n the VA . Over 90n the VA  and cardn the VA ,11 and dn the VA  than theA national conference organized in 2002 by the VA Mental Health Quality Enhancement Research Initiative (MH QUERI) and others developed evidence- and expert consensus-based recommendations for metabolic side-effect monitoring . Subsequi.e., within 30 days before to 30 days after the new prescription date) than at initial follow-up , although at both times monitoring was low. For example, baseline monitoring rates compared to follow-up rates were 67% versus 49% for weight, 46% versus 27% for glucose or hemoglobin A1c, and 32% versus 16% for LDL [Both VA ,20-22 anA previous project, ‘A Study of Strategies for Improving Schizophrenia Treatment (ASSIST),’ compared the effectiveness of two strategies aimed at improving medication management for schizophrenia – a team-based quality improvement strategy (Team QI) and a strategy involving a single clinical opinion leader (OL) at six sites in two Veterans Integrated Service Networks (VISNs). Both strategies were aided by an evidence-based QI (EBQI) approach and external facilitation (EBQI/F). While both Team QI and OL strategies resulted in improvements in metabolic monitoring rates at the time of a new antipsychotic prescription, neither strategy was clearly superior to the other. The study suggested that: designating a provider or clinic to ensure completion of monitoring, and implementing a computer routine that queried the VA electronic medical record to identify patients due for monitoring were effective QI components.e.g., 88% of patients had an FPG test in the past year) because of longer observation periods than in other studies. For obese or overweight patients (82% of the sample), 21% did not have any record of a weight management intervention. Of the 17% of patients with elevated glucose in the past three years, only 49% had documented management. A limitation of this study was that it looked at any metabolic management within the past year, rather than examining timely intervention for abnormal monitoring results. The OIG report and VA research clearly demonstrate the need for more timely guideline-concordant management of antipsychotics’ metabolic side effects.Subsequently, in December 2007, the VA Office of Inspector General (OIG) reported on their examination of metabolic monitoring and management for patients on atypical antipsychotics for ≥90 days . Rates oAlso in 2007, MH QUERI and the South Central Mental Illness Research, Education and Clinical Center (MIRECC) sponsored an expert panel meeting to further operationalize metabolic monitoring recommendations and consider applicability of the other VA/DoD CPG recommendations for management of metabolic side effects. Panel discussions informed a subsequent task force, the Atypical Antipsychotic Workgroup, formed by VA Mental Health Services in 2008. Both groups, after review of existing guidelines and relevant scientific literature, noted the importance of broad dissemination of evidence-based and expert consensus-based recommendations for monitoring and managing antipsychotic side effects.Following the Atypical Antipsychotic Workgroup report, Mental Health Services funded the MIRECC Initiative on Antipsychotic Monitoring Improvement (MIAMI) Project to broadly disseminate metabolic monitoring and management recommendations along with promising tools, strategies, and technical assistance to support relevant quality improvement efforts. The MIAMI Project team included clinical and research experts in psychopharmacology, SMI, and implementation science, who further operationalized metabolic monitoring and management recommendations. The MIAMI Project included:1. A national training meeting (May 2010) attended by approximately 100 providers and clinical managers;2. The MIAMI Project Technical Assistance Center (TAC) to assist providers and clinical managers in developing quality improvement efforts and to provide additional information on MIAMI Project tools/resources; andhttp://vaww.mirecc.va.gov/miamiproject), with links to relevant clinical practice guidelines, educational resources, and weight management resources.3. A VA intranet website .2. To test the effect of the EBQI/F intervention as an augmentation to the national implementation initiative on management of metabolic side effects of antipsychotics in sites likely to encounter greater challenges to implementation.3. To assess the direct costs of the EBQI/F intervention, and explore potential variations in costs of the EBQI/F intervention in sites with lower versus higher levels of organizational challenges.This study employs a cluster randomized clinical trial design, with matched pairs of VA facilities defined as the clusters, to test the effectiveness of an EBQI plus facilitation (EBQI/F) intervention combined with the ongoing national quality improvement initiative (MIAMI Project) at six sites (intervention sites) compared to six matched comparison sites exposed to the national quality improvement initiative alone (control sites). The extent to which metabolic monitoring and management recommendations are followed will be examined at the intervention sites over three six-month intervals: the Pre-implementation Phase, defined as the six-month period prior to the initial EBQI site visit at the intervention sites; the Implementation Phase, which includes active external facilitation (EBQI/F); and the Sustainability Phase, during which the research team continues to evaluate the extent of metabolic monitoring and management, but external facilitation is not provided . Three of the 24 sites were excluded because of an active or planned research project to study metabolic monitoring and/or management. Two sites were excluded because they already had primary care clinicians integrated into mental health clinics. Two sites declined to participate, and leaders at three other sites did not respond to repeated requests for participation in the project. Leaders at the remaining 14 sites attended conference calls with the study PI to obtain further information, and each agreed to have their site included in the final site selection pool. Each completed a brief survey, adapted from a VA Clinical Practice Organizational Survey that included questions on provider stress and ability to pursue practice change ,35. SurvStudy participants include VA employees who are involved in the monitoring and management of patients treated with antipsychotics at participating sites and who completed surveys and interviews about related practices and quality improvement efforts; and VA patients prescribed antipsychotic medications, whose administrative and medical record data are obtained and analyzed to assess metabolic monitoring and management rates throughout the study. Employee participants were recruited solely by the research team to ensure confidentiality and avoid coercion. The study was reviewed and approved by the VA Central IRB and the Central Arkansas Veterans Healthcare System Research & Development Committee.Promoting Action on Research Implementation in Health Services (PARIHS) is the conceptual framework that guides and informs our intervention and evaluation approaches for this study. In this framework, successful implementation (SI) is represented as a function (f) of the nature and type of evidence (E), the qualities of the context (C) in which the evidence is being introduced, and the way the process is facilitated (F): SI = f . ‘EvidenThe EBQI/F intervention, which involves researchers partnering with clinical stakeholders, is designed in a manner that is consistent with available research evidence and reflects the knowledge and expertise of site participants regarding how to tailor the strategy to local needs, priorities and resources. The intervention combines: EBQI processes in the EBQI Design Phase to design and tailor the initial implementation strategy to the local context, and external facilitation to support, monitor, problem-solve and refine implementation (as needed) during the study’s Implementation Phase. Further, through combining strategies and tools included in the MIAMI Project (see above) with EBQI and facilitation, the EBQI/F intervention provides a multifaceted approach to improving care in this area -41.e.g., prescription of a hypoglycemic agent following an elevated glucose test). The research team obtained approval from the VA Office of Information & Technology to install this software at study sites.For the current project, the automated computer routine that was developed during the ASSIST Project (see above) was revised to identify patients who had been prescribed a new antipsychotic medication and were due for baseline or initial follow-up monitoring. Reports generated by this routine list weight, BMI, and relevant laboratory test results, if these tests were done. Additional computer routines were developed to generate a list of patients with abnormal laboratory results, and indicate whether management actions had been taken  involved in monitoring and managing patients treated with antipsychotics who were identified based on discussions between the study PI and site mental health leaders.EBQI participants at each intervention site include approximately two to four key staff , such as current practices, barriers/facilitators, key issues, and potential solutions in addressing project goals. These data were gathered through qualitative interviews conducted prior to the start of implementation activities, analyzed using a rapid analysis approach ,43, and During the EBQI Design Phase, EBQI participants consider the QI tools/resources included in the MIAMI Project as well as additional monitoring and management tools and strategies that may be useful for local implementation. The duration of the EBQI Design Phase varies across sites, an understandable phenomenon in implementation studies, where preparation, design and implementation are often classified as distinct phases and differ depending on activities at each intervention site .The Implementation Phase of this study is guided by an experienced and well-respected researcher (JLS), who serves as the lead facilitator, and a co-facilitator. Facilitator roles are to establish and leverage relationships with clinical stakeholders in order to encourage, support and guide them in executing the local implementation strategy.It is expected that specific facilitation activities will vary by site because the context/needs of individual sites will also vary, while the roles of the facilitator will remain consistent with key components of external facilitation—including interactive problem-solving and support—as identified in our earlier MH QUERI research . A time/Evaluation will include formative and summative evaluation activities. Formative evaluation (FE) is designed to identify potential and actual influences on the progress and effectiveness of implementation efforts. It also helps optimize the potential for success by providing a better understanding of the processes involved, identifying and addressing needed refinements to the implementation strategy, and assessing the merit of using similar approaches in future implementation efforts . The FE The objectives of developmental FE are to identify determinants of current practice regarding monitoring/management of metabolic side effects, identify available QI resources, identify barriers/facilitators, and engage clinical stakeholders in defining key issues and potential solutions in addressing project goals. Key staff at intervention and control sites have completed semi-structured telephone interviews, providing their perspectives on these issues. Participants also completed the Organizational Readiness to Change Assessment (ORCA), described below.The objectives of implementation-focused FE are to document implementation processes and exposure of site participants to the intervention, identify barriers to and deviations from the planned local implementation strategy, and modify the strategy as needed to overcome barriers . The objThe objective of interpretive evaluation is to obtain stakeholder perspectives on the perceived value of the EBQI/F intervention, barriers and facilitators encountered, satisfaction with the implementation process, unintended consequences, and any needed refinements. Only intervention sites receive interpretive evaluation.Stakeholder experiences with the intervention will be assessed after the Implementation Phase through semi-structured qualitative telephone interviews with the two most involved participants in implementation activities at each EBQI/F site. All interviews will be audio-taped and transcribed for qualitative data analyses.Summative evaluation data sources include data extracted from VA databases; medical record abstraction; and surveys  administered to the participants. The VA datasets contain patient demographics, inpatient and outpatient encounters and associated diagnoses, pharmacy and laboratory data, and vital signs. Patient data on metabolic side-effect monitoring and management will be collected on all Veterans meeting inclusionary criteria at each site, and these data will be analyzed and presented at the VA facility level.Data will be extracted for all patients who were treated at a study site and were prescribed a new antipsychotic medication   and who e.g., 126 mg/dL for glucose). However, diabetes practice guidelines indicate that two random glucose tests with results ≥200 mg/dL may be used to diagnose diabetes [Performance of recommended management actions will be assessed for patients with evidence of obesity (BMI ≥30), hyperglycemia (plasma glucose ≥200 mg/dL), elevated hemoglobin A1c (≥6.5), or elevated LDL (≥160 mg/dL) at either the baseline or 90-day follow-up window, or weight gain (>5% gain from baseline) at the 90-day follow-up window. Because VA datasets do not contain a reliable indicator of whether a laboratory test was performed when the patient was in a fasting state, these thresholds for management are set at a higher level than indicated in practice guidelines  are listed in Table A number of patient demographic and clinical characteristics could affect the frequency of vital sign determinations and laboratory tests for glucose or lipids. For example, patients with chronic heart failure should have weight recorded frequently; patients with diabetes would have more frequent fasting plasma glucose tests; and older patients and patients that have frequent primary care visits for any reason would also be more likely to meet criteria for recommended metabolic monitoring. Therefore, in addition to birth date, gender and race, we will extract diagnostic codes to identify pre-existing diagnoses of overweight/obesity, diabetes or dyslipidemia, as well as other physical comorbidities. These variables, summarized over site, will be included as covariates in the statistical models of monitoring and management.The effect of organizational readiness-to-change on implementation is being measured in this study with the Organizational Readiness to Change Assessment (ORCA) . This inTo estimate direct intervention costs (Objective 3), we adapted the methodology used in the Translating Initiatives in Depression into Effective Solutions (TIDES) study . We wille.g., for EBQI/F sites, is the monitoring performance change during the Implementation Phase different from that during the Sustainability Phase? We will similarly collect, summarize, and analyze data from all patients due for follow-up metabolic monitoring and metabolic management ; that is, each site has its own slope, but sites within the same intervention group tend to be more alike than those from the other intervention group. The RCR will also allow the slopes to change with the phase of the study, thus allowing us to also test whether performance change differs among the phases over the study. For example, performance change during pre-implementation is expected to be unchanging or flat, but is expected to increase or trend upward once EBQI/F begins.We will compare the performance change over time (a slope) between EBQI/F and control sites using a random coefficients regression (RCR) that accounts for repeated measures taken within a site  and the number of hours spent (person hours), with separate estimates for clinical QI and research team activities. We will also explore whether there may be potentially meaningful variations in costs/intensity of the EBQI/F intervention at the EBQI sites based on their readiness-to-change, using data collected from the ORCA.i.e., within-phase performance change) and changes in slopes (between phases) assuming first: low, medium and high values for the residual standard deviation (σ), the variances of the random intercepts (va) and slopes (vb), and a first order auto correlation, ρ, among the observations within a site; then, power of at least 0.8 on a two-sided test made at the 0.05 significance level. Using ASSIST study findings, we estimated residual standard deviations (σ) ranged from 8.9% to 11.9%, va from 53.4 to 167, vb from 4.4 to 6.6, and within-site first order auto correlations (ρ) from 0.10 to 0.53. We used the minimum, midrange, and maximum of the estimates to respectively present best case , expected , and worst case , scenarios. Given the low rates of metabolic monitoring and management observed in preliminary studies, the detectable changes would be both possible and clinically meaningful.Based on our six EBQI/F intervention sites and six control sites, Table The study is in the initial part of the Implementation Phase. The initial EBQI site visits to the six implementation sites were completed in 2012, and facilitation activities have begun at the intervention sites. Retrospective data are now being collected from all study sites.This study will build on prior research, demonstrating the effectiveness of EBQI and facilitation to support tailored implementation efforts at a site, and addresses an important aspect of clinical care for patients taking antipsychotics. Improving monitoring for metabolic side effects of antipsychotics, as well as promoting timely evidence-based management when these effects emerge, will lead to improved patient safety and long-term outcomes. This project aims to increase uptake of the existing tools and strategies that have been made available through a national dissemination effort, although the facilitation process could result in refinements of these elements or in development of new improvement approaches. We discuss strengths and initial challenges of the study below.The research team employed a systematic site selection process rather than identifying a convenience sample of frequently-utilized study sites. The selected sites thus are more likely to be representative of the diversity of VA facilities, with respect to size, extent of academic affiliation, resources available to pursue quality improvement efforts, and scores on the organizational practice survey than would have been the case if a convenience sample of sites was selected. Systematic site selection ensures that study findings will be broadly generalizable to the majority of VA facilities, and enables the research team to identify unique site implementation barriers and facilitators.e.g., because the leader who originally agreed was no longer in the same position). This experience suggests that a disadvantage of the systematic site selection process is that there may be more attrition than when convenience sampling is employed; perhaps investigators could develop retention strategies to maintain site leaders’ interest in the study and encourage them to overcome participation barriers during the sometimes lengthy waiting period between grant submission and final funding. A study team could include back-up sites in the site selection approach, although it may not be possible to activate a replacement site once the study has started. Finally, investigators should recognize that a site that withdraws after the start of implementation activities should still be included in an ‘intent-to-implement’ analysis.Despite the potential benefits of this site selection method, it also has caused challenges. While we pursued IRB approval, our contacts at 3 of the 12 initially selected sites indicated that the site would be unable to participate in the study  [Evidence- and consensus-based guidelines recommend obtaining plasma glucose and lipid tests in the fasting state, and intervening if test results are elevated (0 mg/dL) ,18. Unfo0 mg/dL) . Therefo0 mg/dL) ; or examWe also chose to focus our Objective 2 examination of management actions on those patients whose testing indicated obesity (BMI ≥30) or weight gain (>5%), rather than including the larger group of patients who warrant management for being overweight (BMI between 25 and 30). It would not be feasible to review the medical records for all patients with BMI greater than or equal to 25. Excluding these patients, as well as patients with possible abnormal glucose or LDL values, represents a limitation in the study methods. We will further explore this issue by conducting a sensitivity analysis by assessing the extent to which side-effect management takes place for a subsample of patients who are overweight, have blood glucose between 126 and 200 mg/dL, or have LDL between 130 and 160 mg/dL. We will also explore whether chart documentation indicates that a given blood test was meant to be obtained while the patient was fasting. These sensitivity analyses could provide useful information for future studies and could be used to encourage inclusion of fasting notations in the VA databases.Despite the challenges and limitations of this complex study of implementation strategies, this ongoing study will yield insights into barriers and facilitators to monitoring and management of antipsychotic side effects; determine the effectiveness of EBQI combined with external facilitation with regard to promoting successful implementation; and hopefully will improve care and patient safety at the intervention sites. Study findings will inform subsequent VA efforts to improve care and safety for patients prescribed antipsychotic medications.ASSIST: A study of strategies for improving schizophrenia treatment; ADA: American diabetes association; APA: American psychiatric association; BMI: Body mass index; CATIE: Clinical antipsychotic trials of intervention effectiveness; CPG: Clinical practice guidelines; DoD: Department of defense; EQUIP: Enhancing quality and utilization in psychosis; EBQI/F: Evidence-based quality improvement with facilitation; FPG: Fasting plasma glucose; FE: Formative evaluation; LDL: Low-density lipoprotein; MH QUERI: Mental health quality enhancement research initiative; MIRECC: Mental illness research, education, and clinical center; MIAMI: MIRECC initiative on antipsychotic monitoring improvement; OIG: Office of inspector general; OL: Opinion leader; PARIHS: Promoting action on research implementation in health services; SGA: Second-generation antipsychotic; SMI: Serious mental illness; SMM: Survey on metabolic side-effect monitoring and management; VistA: Veterans health information systems and technology architecture; VISN: Veterans integrated service network.The authors declare that they have no competing interests.All authors have made substantial contributions to the study conception and design, as well as to the development and editing of the manuscript. RO and JS led the initial study design and development and wrote the original study protocol. RL planned the statistical analyses and performed the power analysis. KD, KM, and SP assisted with further refinement of the study protocol. RO and SP drafted the publication with contributions from all authors. All authors are contributing to the conduct of the study and have read and approved the manuscript for publication.Detailed Description of Data Analysis Methods for Objectives 1 and 2 Time Series Analysis.Click here for file


Non-communicable diseases (NCDs) are estimated to be the leading causes of morbidity and mortality in developing countries, especially Africa -3. AboutA long-term goal of the organizers of the conference is to make cancer a top priority in Africa. In pursuit of this goal, the objective of this workshop was to train cancer advocates who will be empowered to engage their communities, develop, and implement cancer health and survivorship programs. The workshop was designed to provide participants with the skills to: (1) mobilize the resources within African countries for health promotion, prevention, and survivorship strategies; (2) partner with key stakeholders to accomplish targeted objectives; (3) raise funds to support advocacy activities; and (4) develop and successfully organize community-centered programs. The specific objectives for the participants included to:1. Provide opportunities for mutual learning, knowledge transfer, and collaborations among cancer advocates. Participants were provided with learning opportunities to:a. Assess and track the cancer health needs of their communities;b. Conduct a SWOT analysis to develop effective strategies, including the development of a local community action plan;c. Initiate and develop partnerships with other stakeholders to address the needs of their communities;d. Organize and implement programs to: (i) raise public awareness about cancer, (ii) provide support to those living with cancer, (iii) help advance cancer research and training, (iv) improve the quality of cancer care, and (v) address legislative and regulatory issues that affect cancer care and research in Africa; ande. Utilize evaluation tools to determine, document, and improve the program outcomes of programs implemented in their communities.2. Facilitate networking among individuals involved in cancer control, education and research in Africa.3. Facilitate the development of a global community of practice to address common challenges in cancer advocacy in Africa.4. Contribute to a global impact against cancer through advocacy.® and the African Organisation for Research and Training in Cancer (AORTIC) in partnership with several other organizations including the National Cancer Institute and World Wide Prostate Cancer Coalition. The conference was held in Cairo, Egypt on November 29, 2011. A total of 73 delegates participated in the conference including delegates from Africa, the Caribbean, the United Kingdom, Italy, Germany, Canada, and America. Thirty delegates representing thirteen African countries were selected as recipients of scholarship funding.The International Workshop on Cancer Advocacy for African Countries (CAAC) was organized by the University of Florida, the Prostate NetOpening Session began with opening remarks and a welcoming of the workshop delegates by Professor Folakemi Odedina (Conference Chair) and a program overview provided by Mr. Virgil Simons (Conference Co-Chair). The opening presentation titled “Setting the Stage for Cancer Advocacy in Africa: What and Why?” was given by Professor Odedina (USA) and Mr. Simons (USA). Professor Odedina offered insights based on her experiences in Nigeria and elsewhere in Africa in developing cancer advocacy initiatives, including the establishment of a National Cancer Awareness month in Nigeria and other advocacy efforts such as organizing Cancer Control meetings at the local, regional, national and international levels and conducting media programs to educate the public on cancer and raise awareness. Their presentation also covered the principles of advocacy and types of advocacy appropriate for cancer control.The oundtable Discussions on best practices for cancer advocacy. This session, presided by Professor Ogunbiyi (Nigeria), involved six roundtables: support advocacy presided by Kandusi (Tanzania), community outreach advocacy presided by Bekele (Ethiopia), education advocacy presided by Kamara (Sierra Leone), political advocacy presided by Daramola (Nigeria), research advocacy presided by Mapara (Zimbabwe), and fundraising advocacy presided by Stevn (South Africa). Following the roundtable discussions, the presiders for each roundtable reported a set of action items resulting from the discussions, which is summarized as part of the proceedings.This presentation set the stage for small group RUnderstanding Your Community and Assessing your Community Health Assets and Needs.” Her presentation addressed the actions steps necessary for conducting a needs assessment including assembling the community team, developing a team strategy, reviewing community sectors, gathering, entering, reviewing data, and building a community action plan. She concluded her presentation by reminding the delegates that if the problems are in the community, the solutions are also in the community.Professor Odedina (USA) described the importance of conducting locally-based needs assessments in the area of cancer control and the process used for performing these assessments in her presentation titled “Partnering with Elected Officials to Advocate Cancer-Related Policies” was given by former Senator Anthony Hill Sr. . Senator Hill’s presentation offered insights to the political process in the USA and how cancer advocates can best position their messages for action by politicians. Scott Williams (USA), representing the Men’s Health Network, presided over a Prostate Cancer Roundtable on the topic of Gaining Political Advantage. Mr. Williams discussed the role of non-profit organizations in forming health prevention messages and developing initiatives especially in the area of cancer control. This presentation was followed by Professor Tim Rebbeck (USA) and Virgil Simons (USA) discussing the importance for cancer advocates and the research community to develop strategic partnerships in a presentation titled “Finding the Lethal Phenotype: Research Partnership Needs.” Professor Rebbeck discussed what is needed to develop research capacity in Africa, emphasizing the need for dedicated influential local principal investigators (PIs), an environment that fosters PIs, research goals which are achievable with a realistic timeframe, and strong mentors with bi-directional visits between mentors and local PIs.The workshop also examined how cancer advocates may engage politicians and researchers. The keynote presentation titled “Engaging the Media & Promoting Your Program.” The next discussion was led by Professor Folakemi Odedina and Mr. Virgil Simons on the formation of the African Cancer Advocacy Consortium (ACAC) at this workshop. They noted that the mission is making cancer a top priority in Africa and described the organization of ACAC, noting six types of advocacy groups comprising ACAC: (1) political advocacy, (2) education advocacy, (3) research advocacy, (4) fundraising advocacy, (5) support advocacy, and (6) community outreach advocacy. An interim ACAC Advisory Board was identified and a chair and co-chair for each advocacy group was selected.In the next session, Professor Renee Reams (USA) described methods she has used to engage the media to promote health prevention initiatives in a presentation titled “The workshop closed with the program assessment and feedback conducted by Professor Richard Segal (USA). Participants provided their evaluations on the overall program, the workshop sessions, and the speakers. In addition, feedback was obtained on suggested improvements for the 2013 workshop. Before closing the workshop, delegates were invited to join one or more of the advocacy groups.The authors have no competing interests to be declared for this manuscript.


Background: Coronary heart disease is the major cause of morbidity and mortality in the world. Psychosocial factors such as depression and low social support are established risk factors for poor prognosis in patients with heart disease. However, little is known about the hypothetical relationship pattern between them.Purpose: The purposes of this narrative review are (1) to appraise the 2002–2012 empirical evidence about the multivariate relationship between depression, social support and health outcomes in patients with heart disease; (2) to evaluate the methodological quality of included studies.Method: PubMed and PsychINFO were searched for quantitative studies assessing the multiple effects of low social support and depression on prognosis outcomes in patients with heart disease. The following search terms were used: *, cardiac disease, support quality, relationship, and relational supportsocial relation.Results: Five studies  were selected and coded according to the types of support . The majority of findings suggests that low social support/being unmarried and depression are independent risk factors for poor cardiac prognosis. However, all analyzed studies have some limitations. The majority of them did not focus on the quality of marital or social relationships, but assessed only the presence of marital status or social relationship. Moreover, some of them present methodological limitations.Conclusion: Depressive symptoms and the absence of social or marital support are significant risk factors for poor prognosis in cardiac patients and some evidence supports their independence in predicting adverse outcomes. Cardiac rehabilitation and prevention programs should thus include not only the assessment and treatment of depression but also a specific component on the family and social contexts of patients. The World Health Organization  reports *, cardiac disease, support quality, relationship, and relational supportsocial relation, alone and in combination. In particular, target articles were searched using the following associations: ab AND ab(cardiac disease), ab(relation* support) AND ab(cardiac disease), ab AND ab(cardiac disease), ab(cardiac disease) AND ab(relationship), ab(cardiac disease) AND ab. After screening abstracts and removing reviews (1%), comments (4%), studies about standardized measures (1%), cross-sectional studies (4%), studies on healthy subjects and studies not concerning the multivariate relationship between depression, social support, and cardiac disease outcomes (84%), full-texts of remaining papers were retrieved and screened for final inclusion. No further paper was discarded and five studies  were ultimately included in the narrative review  and those without  depressive symptoms and into groups of married  and non-married . Marital status was found to be an independent predictor of event-free survival, even after controlling for depressive symptoms and other covariates  referred to a cardiac rehabilitation phase II program, a comprehensive program offering exercise, health education, and psychosocial interventions. Prior to intervention, participants completed a battery of health and psychosocial questionnaires. The baseline and post treatment physical functioning was assessed by the Quality of Life After Myocardial Infarction (QLMI) scale, a valid, and reliable instrument to measure several specific areas of functioning, including cardiac symptoms, physical restrictions, confidence, and self-esteem , medium , and high  for primary analyses. CHD events were identified via hospital/nursing home discharge reports and death certificates. Follow-up interview included the question, “In general, how many relatives and friends do you have that you feel close to? These are people whom you feel at ease, can talk to about private matters, and can call on for help.” This question was used as a proxy measure of social networks to ensure that effects of loneliness are not simply reiterating the well-known relationship between social networks and disease. Findings showed that loneliness predicted incidence of CHD events, even after adjusting for demographic, behavioral and biological risk factors as well as for depressive symptoms and number of close friends and relatives  and cardiac disease outcomes were described. Although findings are mixed, the majority of them (see Table In only one study (Shen et al., In conclusion, very few quantitative studies concerning the multivariate relationship between social support, depression and heart disease outcomes were published from 2002 to 2012. Regarding the positive role of the quality of relationships, it would be desirable that future research and clinical protocols consider the psychological aspects of cardiac patients (Compare et al., Depressive symptoms and social support may be taken into account by nurses, psychologists, and physicians to structure effective interventions, with the aim of improving health outcomes and reducing the risk of mortality and morbidity in cardiac patients. During the evaluation and waiting list for heart surgeries and interventions, relatives, and friends may help cardiac patients to cope with physical disability, limitation of personal autonomy and with a sense of uncertainty about the future. It was proposed in the literature to extend psychosocial interventions aimed at improving mental health, quality of life, and compliance after a cardiac event to family caregivers (Dew et al., The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Christoph Steininger and colleagues explore how multiple infectious, autoimmune, metabolic, and neoplastic diseases have been associated with changes in the intestinal microbiome, although a cause-effect relationship is often difficult to establish. Integration of metagenomics into clinical medicine is a challenge, and the authors highlight clinical approaches that are of high priority for the useful medical application of metagenomics.Please see later in the article for the Editors' Summary Multiple infectious, autoimmune, metabolic, and neoplastic diseases have been associated with changes in the intestinal microbiome, although a cause–effect relationship is often difficult to establish.Here we discuss the problems, applications, and visionary requirements for the integration of microbiome analysis into clinical routine diagnostics.Metagenomics is increasingly used for the culture-independent and largely unbiased characterization of complex bacterial habitats at high resolution. The versatility and decreasing costs of metagenomics make this technology an interesting tool for clinical diagnostics.Methodological shortcomings still impede the application of metagenomics in clinical diagnostics.Integration of metagenomics into clinical medicine requires accepted and validated strategies for (1) translation into clinical action items; (2) sample collection, preparation, and testing; and (3) data analysis and interpretation. We highlight tasks that are of high priority from a clinical perspective for the useful medical application of metagenomics.Escherichia coliThe intestine is one of the most diverse and complex bacterial habitats of the human body, harboring ∼1,000 bacterial phylotypes http://www.metahit.eu) and the US National Institutes of Health Human Microbiome Project (http://www.hmpdacc.org) have set new standards for the in-depth metagenomic characterization of the healthy human microbiota (microorganisms living inside and on humans) from different body habitats Our understanding of the human intestinal microbiome in health and disease has been revolutionized by the development of next generation sequencing and its application to metagenomics, which is the term generally used to summarize culture-independent technologies that allow the characterization of a microbiome Optimizing patient outcome according to metagenomic information depends on the quality of the available information, options for translation of this information into clinical action, and the effectiveness of communication. Translation of metagenomic knowledge into clinical practice is impeded by several limitations. For example, vast amounts of information are generated by metagenomics, which has to be assorted, interpreted, and communicated to clinicians in a comprehensible format. Most clinical studies have focused on characterizing the human microbiota by its taxonomic composition using 16S rRNA–based bacterial surveys, although similar biological functions may be exerted by unrelated taxa Strategies still remain to be defined for (1) translation into clinical action items with impact on patient outcome; (2) sample collection, preparation, and testing; and (3) data analysis, interpretation, and communication. Here, we highlight the tasks that are of high priority from a clinical perspective for the useful application of metagenomics in clinical medicine.Faecalibacterium prausnitzii and other beneficial butyrate-producing bacteria Metagenomic information has been associated with specific disorders in several studies. For example, clinical observations have long suggested that the intestinal microbiome plays a critical role in the pathogenesis of inflammatory bowel disease (IBD) (Crohn disease and ulcerative colitis): (1) inflammation in Crohn disease disappears if the involved bowel segment is excluded from the fecal stream and recurs after re-anastomosis with reexposure to intestinal contents F. prausnitzii in chronic intestinal inflammation While current evidence strongly suggests that the pathogenesis of IBD could be linked to the intestinal microbiota, important clinical questions remain unanswered. So far, study results analyzing microbiome changes in IBD patients were not controlled for potential confounders such as mucosal inflammation per se Hence, metagenomics approaches have to fulfill several clinical prerequisites to have a significant impact on diagnostic, prophylactic, and therapeutic strategies. A cause–effect relationship between a defined disorder and intestinal microbiome profile has to be established beyond doubt. A clear distinction between intestinal microbiome profiles of disorders  on the basis of metagenomic information would greatly facilitate diagnostic strategies. Identification of significant confounders of metagenomic information  may also help in devising novel prophylactic strategies. Well-directed strategies for the targeted therapy of disorders of the intestinal microbiome have to be developed, and existing ones optimized . For this purpose, longitudinal studies with well-defined intervention and control groups as well as adequate follow-up periods are warranted. Metagenomic information on longitudinal changes in the intestinal microbiome needs to be combined with other clinical and laboratory sources of evidence for translation into targeted therapies.Accurate sample collection, preparation, and analysis are of paramount importance for the characterization of the intestinal microbiome in health and disease. Collection of stool samples; collection of gastric, intestinal, or biliary fluid; and endoscopic mucosal biopsies are routine clinical procedures. Next generation sequencing already allows characterization of the microbial composition of a sample  and of its genetic and functional potential  long analysis times, (2) evolving definitions of reference microbiota, (3) missing standards of analysis methods, algorithms, and databases, (4) lack of well-defined physiological ranges, and (5) missing evidence for cause–effect relationships.http://humanfoodproject.com]). This information would also provide the basis for establishing cause–effect relationships. Finally, reference values have to be updated continuously and integrated into analysis algorithms for effective translation of evolving insight into intestinal microbiota into clinical practice.From a technical perspective, a maximum level of automation would facilitate the digest of metagenomic data into clinically meaningful information. Analysis speed is highly dependent on the number of collectively analyzed samples, and the methods and tools used. Filtering and quality improvement steps may require several days, even on medium-sized computing clusters. Hence, rapid data analysis needs a reference microbiome as a reliable standard with which to compare individual samples, reduction of analysis complexity, and, ultimately, integration of analysis algorithms and desktop sequencers into a single package. Furthermore, for meaningful interpretation and communication, results of statistical evaluations should be generated and digested into clinically relevant bits automatically in the same sequencing unit, and communicated as an analysis report to the physician within a few hours. A crucial biological point is the definition of physiological ranges of gut microbiota parameters, which are highly variable between ethnic groups, geographic locations, and different diets The establishment of characteristic and thoroughly validated signatures of the intestinal microbiome allows the development of new prophylactic, therapeutic, and prognostic strategies for beneficial and targeted modification of the patient's intestinal microbiome. Most metagenomic tools required for addressing these important questions are already available, standard operating tools are under development (see the Human Microbiome Project), and insight into the human microbiome is evolving rapidly . Modern,Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, et al. (2010) A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464: 59–65. This study reports a large-scale approach to characterizing the functionality of the intestinal microbiota by cataloging human gut microbial genes, which is a prerequisite for defining health and disease states in terms of the microbiome.Human Microbiome Project Consortium (2012) Structure, function and diversity of the healthy human microbiome. Nature 486: 207–214. This project is a trendsetting approach to establishing comprehensive metagenomic datasets of  body habitats as reference datasets and to lay the foundation for the translation of metagenomic research into diagnostic applications.Kump PK, Gröchenig HP, Lackner S, Trajanoski S, Reicht G, et al. (2013) Alteration of intestinal dysbiosis by fecal microbiota transplantation does not induce remission in patients with chronic active ulcerative colitis. Inflamm Bowel Dis 19: 2155–2165. This was one of the first attempts not only to use FMT but also to characterize the procedure and the outcome by metagenomics.Ley RE, Turnbaugh PJ, Klein S, Gordon JI (2006) Microbial ecology: human gut microbes associated with obesity. Nature 444: 1022–1023. This study links the metagenomics pattern of the human intestinal microbiome to a clinical disorder and is therefore of importance for therapeutic approaches.Navas-Molina JA, Peralta-Sánchez JM, González A, McMurdie PJ, Vázquez-Baeza Y, et al. (2013) Advancing our understanding of the human microbiome using QIIME. Methods Enzymol 531: 371–444. This study describes one of the common interactive analysis tools for microbiome analysis currently used by many researchers, which might be used in the future for standardizing data analysis.


Background: Fat-rich diet may alter oocyte development and maturation and embryonic development by inducing oxidative stress (OS) in follicular environment. Objective: To investigate the relationship between fat intake and oxidative stress with oocyte competence and embryo quality.Materials and Methods: In observational study follicular fluid was collected from 236 women undergoing assisted reproduction program. Malon-di-aldehyde (MDA) levels and total antioxidant capacity (TAC) levels of follicular fluid were assessed as oxidative stress biomarkers. In assisted reproduction treatment cycle fat consumption and its component were assessed. A percentage of metaphase ΙΙ stage oocytes, fertilization rate were considered as markers of oocyte competence and non-fragmented embryo rate, mean of blastomer and good cleavage (embryos with more than 5 cells on 3 days post insemination) rate were considered as markers of embryo quality.Results: The MDA level in follicular fluid was positively related to polyunsaturated fatty acids intake level (p=0.02) and negatively associated with good cleavage rate (p=0.045). Also good cleavage rate (p=0.005) and mean of blastomer (p=0.006) was negatively associated with polyunsaturated fatty acids intake levels. The percentage of metaphase ΙΙ stage oocyte was positively related to the TAC levels in follicular fluid (p=0.046). The relationship between the OS biomarkers in FF and the fertilization rate was not significant.Conclusion: These findings revealed that fat rich diet may induce the OS in oocyte environment and negatively influence embryonic development. This effect can partially be accounted by polyunsaturated fatty acids uptake while oocyte maturation is related to TAC and oocytes with low total antioxidant capacity have lower chance for fertilization and further development.  The follicular fluid (FF) surrounding the oocytes, plays a critical role in constituting a complex ovarian microenvironment that influences oocyte quality and thereby affects assisted reproduction outcomes. Oxidative stress (OS) refers to overproduction of free radicals and reactive oxygen species which are generated as part of a normal cellular metabolism and/or a deficit in the capacity of antioxidant defense systems, leading to oxidation of biologic macromolecules . SeveralSome external factors, related to life-style, may damage the oocyte competence through an overload of reactive oxygen species. Among these factors, it is known that fat-rich diet is associated with increased serum cholesterol and triglyceride levels and is linked to induction of OS. It has been shown that increased circulating level of low-density lipoproteins induces OS in endothelial cells and such phenomenon lead to systemic pathological process, but limited data are available on the effect of dietary fat intake on the OS in follicular environment and assisted reproduction outcomes -9.Therefore, a change in follicular lipids due to high dietary fat intake may affect the peroxidative process in antral follicle. However, it must be noted that due to the unique characteristics of FF, its composition is different from blood and for this reason the effect of dietary fat on OS in FF needs to be further explored , 11. ConTherefore, to demonstrate the impact of fat intake on the oocyte competence due to induced-OS in FF, the relationship between the dietary fat intake level and lipid peroxidation product in FF, in addition to the relationship between dietary fat intake and oocyte competence, were evaluated. Since, body mass index (BMI), physical activity and smoking status may influence both the OS in FF and oocyte competence, they were referred to as influential parameters.An observational study included 240 consecutive series of in vitro fertilization/intra-cytoplasmic sperm injection (IVF/ICSI) candidates from July 2010 to April 2011 was conducted at Isfahan Fertility and Infertility Center. Institutional Review Board and the Ethics Committee of Tehran University of Medical Sciences approved the study. Informed consents were obtained from all subjects. The inclusion criterion was being aged from 18-40 years old and the exclusion criteria were male factor infertility according to World Health Organization criteria, systemic disease and considerable change in dietary regimen over the previous three months and during assisted reproduction cycle .QuestionnairesAt the start of the medication cycle, characteristics of patients and smoking status were recorded. A validated semi-quantitative food frequency questionnaire (FFQ) including 168 food items was used to measure the calorie intake, total dietary fat, and its components including saturated FAs (SFAs), mono-unsaturated FAs (MUFAs), and poly-unsaturated FAs (PUFAs) over the previous three months . DependiNutritionist software version IV  was used to calculate the daily energy and fat component. The USDA food composition table was used for most items . Physical activity was measured using the original International Physical Activity Questionnaires. This questionnaire assessed the energy expenditure in total, by moderate and vigorous intensity and by using metabolic equivalent (MET) values and formula for computation of MET-minutes , 15. BMIOvulation InductionThe long protocol, involving GnRH agonist and hMG/Gonal F administration, was consistent and follicular maturation was monitored by ultrasound examination. In brief, daily subcutaneous GnRH agonist  was started in the mid-luteal phase of the previous cycle and gonadotropin stimulation of the ovaries commenced on day 2 of last menstrual period, for 12-14 days when transvaginal sonography showed absence of follicles/cysts. For all patients, gonadotropin therapy was initiated with a daily dose of 100-300 IU of either with rFSH  and/or hMG  which was adjusted according to follicular response. Ovulation was triggered with 10,000 IU hCG , when dominant follicles reach a follicular size of around 18 mm. oC, for maximum 2 weeks, until analyzed for malon-di-aldehyde (MDA) and total antioxidant capacity (TAC). The samples without oocyte or contaminated with RBC were discarded. The oocytes were scored for presence or absence of germinal viscule and first polar body. Oocytes were considered fertilized when two pronuclei was observed 17-19 hours post insemination. Numbers of blastomer were defined and percentage of embryos without fragmentation was calculated. 36 hours later, the oocytes were collected transvaginally and used for IVF or ICSI procedure. Despite exclusion criteria of male factors infertility, as routine protocol of Isfahan Fertility and Infertility Center, portion of oocyte were inseminated through ICSI procedure. At oocyte retrieval, fluid from an average of one to 5 follicles of 16 mm diameter or larger was pooled and centrifuged at 300 rpm for 17 minutes, and 2 ml of the supernatant was stored at -70Embryos with more than 5 cells on 3 days post insemination were considered as good cleaved embryos. In ICSI cycles, the percentages of MII stage were calculated by dividing the number of oocytes with first polar body by number of oocytes that were assessed. In IVF/ICSI cycles the percentages of MII stage were calculated by dividing the number of oocytes presenting at least one polar body by the number of oocytes that were assessed. Embryos with less than 5% fragmentation were considered as non-fragmented and percentage of these embryos was calculated.Laboratory analysiset al and TAC was assessed by enhanced chemiluminescence assay as described previously . The normality of the distributions of fat and its components intake levels were assessed by Q-Q plots and found to be skewed. Log transformation improved normality and the values were used throughout the analysis. Descriptive analyses were performed using mean and standard deviation. The data were analyzed using linear regression  and t-test. The p-value of less than 0.05 was considered to be significant. In total, 240 couples participated in the study. Due to ovarian hyper stimulation syndrome, four subjects were excluded from the study. Profiles of subjects are presented in Relationships between the fat components and TAC level in FF were not significant. Association between the oocyte competences and embryo quality markers with biomarkers of stress oxidative in FF, adjusted for age, BMI, physical activity, smoking status and etiology of infertility are presented in The good cleavage rate was negatively related to the MDA levels in FF. Association of the oocyte competence parameters and the fat components intake adjusted for influential factors revealed that the total fat intake and calorie intake from fat were negatively associated with percentage of non-fragmented embryo. Also, the mean of blastomer and the good cleavage rate were significantly and negatively related to the PUFA intake . Although, To answer the question “whether dietary fat intake influences oocyte competence by inducing OS in FF”, three objectives were followed in this study including the relations between the dietary fat intake and OS in FF, the OS in FF and oocyte competence, and the fat intake and oocyte competence. Initially, the result of this study revealed that the relation between the OS in FF and total fat intake was not linear. However, in the women with fat intake of over 40 gr per day, the MDA level was significantly higher than the women with lower fat intake. Therefore, it could be concluded that the oocytes of individuals with dietary fat intake of over 40 grams per day are prone to OS and this might be due to high PUFA intake. Despite the positive role of PUFAs intake on health status at systemic level, which is orchestrated through the balance of LDL/DHL profile, PUFAs are considered as suitable substrates for production of ROS, mainly lipid peroxidation; the byproduct of which is MDA , 18-20. et al showed that there was feeding dairy cow with polyunsaturated FAs, as compared to mono-unsaturated FAs had no positive effect on oocyte quality, and its subsequent embryo development  stage in a dose-dependent manner and adversely affected its subsequent development; however this effect is reversible . In contelopment . et al revealed that exposure of the follicle to n-3 rich PUFA due to maternal dietary of high n-3 PUFA, alters mitochondrial distribution and calcium levels and increases the production of reactive oxygen species (These inhibitory effects may be due to oxidation of PUFA in the cellular membrane which would impair membrane function and structural integrity, and would decrease membrane fluidity which can inactivate membrane bound enzymes or hormonal interaction at membrane level which is important in follicular endocrine function . Indeed, species . et al which showed an association between poor oocyte morphology and increased total fat concentration in FF in individuals undergoing assisted reproduction (Also, our data showed the negative association between the total fat intake and non-fragmented embryo rate. This observation is consistent with a previous report by Jungheim oduction . They fuThe second objective of this study was to evaluate the relation between OS in FF and oocyte competency. The MDA levels showed a negative correlation with good cleavage rate, suggesting that oocytes developed in OS have lower chance to cleave. Consistent with our findings, previous studies reported that elevated reactive oxygen species levels were seen in FF containing embryos of poorer morphology or negative association observed between cleavage rate with protein oxidation levels , 3.Despite our results and others, not all studies in this field have demonstrated a relation between antioxidant defense capacity and oocyte maturation and in regard to this, some researchers have suggested that antioxidants including vitamins A, C and E, despite their antioxidant capacity, may exert their effect on oocyte maturity through other routes , 26-28. This could be a reason that the MDA, rather than TAC depletion, is considered as a better marker of oxidative stress . HoweverGlutathione, as source of antioxidant is essential to oocyte health and play an important role in sperm decondensation post sperm penetration into oocyte , 32, 33.Furthermore, metabolic and hormonal pathways, which could influence oocyte quality can be affected by fat rich diet and it has been shown that foods high in fat are rich in advanced glycation end-products and there accumulation in plasma may increase OS in plasma and FF which is derived from the plasma , 35-44. Despite the aforementioned possibilities, excessive intracellular lipids storage, in term of high lipid droplets within oocyte is considered as a negative factor and has been associated with suboptimal mitochondrial function, hampering the quality and viability of the embryo, especially during cryopreservation , 49. AnoIn conclusion the results of this study suggest that, fat intake over 40 gr per day increases the level of lipid peroxidation as a result of oxidative stress, assessed by MDA. However, among fat component only PUFA showed a significant relation with MDA, suggesting that increased uptake of PUFA prone cumulus oocyte complex to oxidative stress via PUFA which in turn affects the mean of blastomer and quality of embryo. Unlike PUFA, calorie intake improved these parameters and also reduced the embryo fragmentation rate. The results also revealed that lack of antioxidant capacity within follicle would reduce the maturation ability of the oocyte to reach MII, and thereby it has no influence on latter stage since these oocytes are not used for insemination. Furthermore, since embryo quality is affected by both male and female components, lack of assessment of this factor is considered as a limitation in this study.


Food allergy, a significant public health concern in the developed world has developed a forensic context where allergy related personal injury, fatality or criminal non-compliance on the part of a food supplier are issues that have recently come before the UK courts. EU General Food Law (178/2002/EC) and Directive 2000/13/EC (to be consolidated into the proposed Food Information Regulation) address allergen avoidance risks relating to composition, labelling and food safety. The European Framework Directive on Safety and Health at Work (Directive 89/391 EEC and daughter legislation) may also be deployed. Compensation in civil law for loss or damage caused by an allergic reaction to a food supplied, not as requested, or with misleading or incorrect information has also been sought. The authors describe recent such cases dealing with prepacked retail and non prepacked catering situations where contraventions of food law could have resulted in fatalities, and health and safety and civil litigation following deaths from food allergy. The cases came before the civil  courts, magistrates and coroner’s courts. In the absence of a current cure, health protection depends on accurate diagnosis, informed food allergen avoidance and the effective management of symptoms. These strategies depend in turn on the multilayered approaches adopted by clinicians, scientists, food suppliers, allergic consumers (and those who care for them), and regulators. Effective food allergen avoidance depends on the diagnosed consumer knowing what to avoid, being able to access correct ingredients information and to rely on the absence of allergen cross-contamination. Access to ingredients information may be via a label, menu or other printed means, or by enquiring of a staff member who may not always appreciate the implications of such a request or be competent in managing food allergy risks. Lapses in any of these areas may have forensic consequences beyond even their initial (sometimes severe) personal impact.


Multiple sclerosis (MS) is an immune-mediated disease affecting central nervous system (CNS). Although MS is classically considered a white matter (WM) disease, the involvement of gray matter (GM) in the pathogenic process has been confirmed by pathology studies and MRI studies. Impairment of cognitive domains such as memory, mental processing speed, attention, and executive function can occur from the early stage of the disease and tends to worsen over time, despite stable physical symptoms. WM demyelination is moderately correlated with CI, suggesting that probably WM abnormalities alone cannot fully explain the extent of clinical symptoms in MS, including CI. Several MRI techniques have shown the involvement of GM in MS and the association between GM damage, physical disability, and CI. The aim of this review is to provide an overview of CI and GM damage assessed by structural brain MRI. Multiple sclerosis (MS) is an immune-mediated disease affecting central nervous system (CNS), characterized by demyelination and axonal degeneration . The etiCI may affect patients at any stage of the disease, including patients with clinically isolated syndrome (CIS) . A rarelMRI is considered a valuable tool to evaluate the extent of brain damage in MS patients. Many efforts have been made to develop new MRI techniques able to detect not only WM matter lesions but also the extent of normal appearing white matter (NAWM) and gray matter (GM) . The rolIn the last years, the classical view of MS as a WM pathology has been overcome by MRI techniques, able to detect the involvement of GM in the development of the disease. Nonconventional MRI technique showed that GM involvement can precede WM damage and is associated with physical disability and CI –48. ThesPostmortem studies of MS brains have showed that demyelination can occur in every region of the CNS, including WM, cerebral cortex, and deep gray matter . In receGM atrophy represents a marker of degeneration in MS patients. It occurs early in the disease course and tends to progress over time to a greater degree than whole brain and WM atrophy . High-reDuring the course of the disease, cortical and subcortical demyelination has been observed in GM structures, including thalamus, caudate, putamen, globus pallidus, and other structures of the basal ganglia . It has Over recent years many studies started measuring abnormalities in NAGM by using various quantitative MRI techniques such as MTR, T1 relaxation time measurements, DTI, and MRS . The recFollowing Charcot neuropathological studies, the involvement of GM in the pathogenic mechanism of MS has been described . Convent


The evidence supports the effectiveness of lifestyle interventions delivered by nurses in PHC to affect positive changes on outcomes associated with the prevention of chronic disease including: weight, blood pressure, cholesterol, dietary and physical activity behaviours, patient satisfaction, readiness for change and quality of life. The strength of recommendations is limited by the small number of studies within each comparison group and the high risk of bias of the majority of studies.Nurses in primary health care (PHC) provide an increasing proportion of chronic disease management and preventive lifestyle advice. The databases MEDLINE, CINAHL, EMBASE and PsychINFO were searched and the articles were systematically reviewed for articles describing controlled adult lifestyle intervention studies delivered by a PHC nurse, in a PHC setting. Thirty-one articles describing 28 studies were analysed by comparison group which revealed: (i) no difference of effect when the same intervention was delivered by a PHC nurse compared to other health professionals in PHC ( The international rise in obesity rates over the last three decades has been accompanied by an increase in preventable chronic diseases, such as type 2 diabetes, cardiovascular disease, stroke, arthritis and some cancers . InternaNurses are an integral part of any multidisciplinary PHC team and have roles that continue to develop and expand in response to financial incentive, medical practitioner shortages and an imperative to decrease pressure on hospitals –5. NurseLifestyle change interventions focus on increasing healthy behaviours at the individual level and reducing chronic disease risk by controlling physiological variables known to be associated with chronic disease onset. Systematic reviews provide strong evidence that lifestyle interventions are effective in: preventing weight gain in adults who are obese , decreasLittle is known to inform the components of PHC nursing interventions for the prevention and management of chronic diseases associated with obesity. This is the first systematic review to compile the evidence regarding lifestyle change intervention effect, when delivered by PHC nurses, without restricting outcomes to those of cardiovascular disease risk . The aimThis systematic review was conducted and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines ,12.The key question informing this systematic review was: What does the published literature report on the effectiveness of interventions for adults which aim to affect change in lifestyle risk factors for chronic diseases that are associated with overweight and obesity, when these are delivered by a PHC nurse in a PHC setting?Articles were eligible if they: described interventions with a lifestyle change component, were delivered to adults by a PHC nurse in a PHC setting, and reported quantitative outcomes on risk factors associated with obesity including: anthropometric, physiologic, behavioural or psychosocial. Randomized and non-randomized controlled trials (RCTs and non-RCTs) were included.Papers were limited to primary sources, published in English. Articles were excluded if they: did not report outcomes for adults; involved treatment of severe mental health disorders; involved pharmaceutical treatment or if participants were using medications that were likely to affect primary outcomes (e.g. anti-hypertensive when blood pressure was a primary outcome); or involved surgical treatment. Studies reporting effect on smoking cessation or alcohol intake were excluded where this was the main focus of intervention, and included, if there were lifestyle change outcomes of interest, as interventions focused on smoking cessation have been reported elsewhere . ArticleMajor health and medicine databases of published literature, MEDLINE, CINAHL, PsychINFO and EMBASE, were searched in September 2010. The bibliographies of included articles were hand searched to locate articles not catalogued in these databases.The database search strategy  was used to manage the included articles and remove book chapters and theses. The search function was used to exclude articles when the title contained the following keywords that were outside the scope of this review: dialysis, urinary, eating disorder, HIV, oncology, haemodialysis, ulcer, literature review or guideline.Using an inclusion/exclusion criteria checklist, two reviewers (LF and GS) independently screened the title and abstracts of articles resulting in 87% reviewer concordance. Non-concordant articles were resolved by consensus or retained for full-text review if agreement was not reached. Full-text articles were reviewed (GS and LF) using an eligibility checklist. If clarification was necessary, the article was independently reviewed by a second reviewer . Further library searches were conducted using the names of authors of included studies to identify subsequent or preliminary papers for those studies. The paper reporting the post-intervention outcome measures was regarded as the primary source.Data from publication describing included studies were extracted systematically by one reviewer (GS) into a database described elsewhere ,15. No fThe following components of each intervention were recorded for comparative purposes: study design, intervention setting, setting recruitment, the involvement of PHC nurse/s in intervention delivery, personnel training as part of the intervention, behaviour change targets, target participants, participant recruitment, group treatment (comparison and intervention groups), number of contacts, treatment duration and outcomes.The risk of bias was assessed for individual studies according to adequate control of: selection bias or allocation bias, detection bias, attrition bias and reporting bias ,16. EachP < 0.05) different from the comparison group. Outcomes reporting smoking cessation and change in alcohol consumption were not extracted.Comparison groups were often recorded within group changes; however, the outcomes reported here are restricted to outcome measures that were significantly , United States (n = 13), Finland (n = 4), the Netherlands (n = 1) and New Zealand (n = 1).The database search identified 3,491 papers. The review process identified 31 articles describing 28 studies that were eligible for inclusion . These sn = 5) or high (n = 20) risk of bias  to high (n = 5) risk of bias investigated the effect of traditional counselling  compared with screening alone (n = 3) (n = 3)  , favoura (n = 3) ,30 and q (n = 3) . Signifi (n = 3) .Four studies with a high risk of bias reported testing PHC nurse delivery of the same dose of counselling comparing traditional counselling with counselling based on behaviour change theory –34. ThreFour studies with a low  and highFour studies tested the effect of a low dose of counselling (one or two contacts) compared with a higher dose ≥3,  of tradiA prescription for physical activity was delivered by a nurse in one study with a low risk of bias   concludes that changes in physiological measures such as glucose metabolism, lipid levels, blood pressure, as well as weight loss provide indirect evidence of intervention effect on long-term health outcomes , and theThe effectiveness of lifestyle interventions delivered by nurses, given appropriate training, is comparable to delivery by other PHC professionals with no adverse effects ,21. ThisThe USPSTF was unable to locate evidence regarding the effectiveness of screening for obesity alone ,64. HoweThe USPSTF recommends that clinicians offer high intensity counselling  and behavioural interventions to achieve weight loss in obese adults  and reduCounselling for lifestyle change in PHC has traditionally taken the form of advice regarding recommendations to meet guidelines. More recently, behavioural counselling in lifestyle interventions has been based on psychological theoretical frameworks such as the theory of planned behaviour , conceptMany articles did not sufficiently report the methods of randomization, allocation concealment, blinding of outcome assessment, or describe conducting a power calculation to determine target sample size. This may indicate that either of these were not performed, or that they were not reported adequately. Only three of the included articles were considered to have no serious methodological limitations and a low risk of bias. It is necessary to acknowledge the difficulties involved in running RCTs with a low risk of bias in free-living populations, especially those that aim to test the effectiveness of non-pharmaceutical preventive healthcare interventions such as dietary, physical activity or other lifestyle change .Small numbers of participants and high attrition rates may have limited the ability of some studies to reach significance for some outcomes and result in over-reporting of outcomes in the absence of intention to treat analyses. The included studies mainly recruited participants with high motivation to participate and few studies indicated that they used process measures to monitor the realization of intervention delivery. Short intervention duration, lack of long-term follow-up and low variety of outcome measures limited the ability of some interventions to evaluate intervention effect.The heterogeneity of the included studies limited the opportunity for quantitative synthesis of outcome effect. The strength of recommendations is limited by the small number of studies within each comparison group analyses and the high risk of bias of the majority of studies. Authors were not contacted for extra information; hence missing information may reflect reporting bias, not necessarily limitations in the implementation rigour.The evidence supports the effectiveness of lifestyle intervention delivered by nurses in PHC to affect positive changes on a variety of outcomes associated with the prevention of chronic disease associated with obesity including weight, blood pressure, cholesterol, dietary and physical activity behaviours, patient satisfaction and quality of life. Outcomes were significantly higher if nurses provided at least one counselling session following initial screening for health risk.This systematic review synthesizes the best available evidence in the context of informing future lifestyle interventions delivered by nurses in PHC. Further research is needed that: (i) has a low risk of bias; (ii) uses a variety of outcome measures that reflect known risk factors for chronic disease including anthropometric, physiological, behavioural and psychosocial intervention effects; (iii) explores training requirements for effective nurse delivery of lifestyle interventions; (iv) explores the efficacy of counselling using theoretical frameworks for behaviour change; and (v) examines the effect of dose.