Patient self-management interventions for smoking cessation are effective but underused. Health care providers do not routinely refer smokers to these interventions.The objective of our study was to uncover barriers and facilitators to the use of an e-referral system that will be evaluated in a community-based randomized trial. The e-referral system will allow providers to refer smokers to an online smoking intervention during routine clinical care.We devised a four-step development and pilot testing process: (1) system conceptualization using Delphi to identify key functionalities that would overcome barriers in provider referrals for smoking cessation, (2) Web system programming using agile software development and best programming practices with usability refinement using think-aloud testing, (3) implementation planning using the nominal group technique for the effective integration of the system into the workflow of practices, and (4) pilot testing to identify practice recruitment and system-use barriers in real-world settings.Our Delphi process (step 1) conceptualized three key e-referral functions: (1) Refer Your Smokers, allowing providers to e-refer patients at the point of care by entering their emails directly into the system, (2) practice reports, providing feedback regarding referrals and impact of smoking-cessation counseling, and (3) secure messaging, facilitating provider–patient communication. Usability testing (step 2) suggested the system was easy to use, but implementation planning (step 3) suggested several important approaches to encourage use . Pilot testing (step 4) in 5 practices had limited success, with only 2 patients referred; we uncovered important recruitment and system-use barriers .Implementing a system to be used in a clinical setting is complex, as several issues can affect system use. In our ongoing large randomized trial, preliminary analysis with the first 50 practices using the system for 3 months demonstrated that our rigorous preimplementation evaluation helped us successfully identify and overcome these barriers before the main trial.Clinicaltrials.gov NCT00797628; http://clinicaltrials.gov/ct2/show/NCT00797628 (Archived by WebCite at http://www.webcitation.org/61feCfjCy) Smoking is the number 1 behavioral health problem and preventable cause of death in the United States . Among iBecause the majority of smokers (70%) see a provider at least once per year , point-oThis paper describes the preimplementation evaluation of a provider e-referral system (ReferASmoker.org). ReferASmoker.org will be used in a nationwide randomized trial that will recruit 160 primary care physician practices and test the e-referral functions . A systeReferASmoker.org is a point-of-care e-referral portal that allows providers to e-refer smoking patients to an online smoking-cessation portal. The ReferASmoker.org system (http://www.ReferASmoker.org) can be accessed using the email address reviewer@nih.grant and the password “review”.Our four-step usability and pilot testing approach consisted of (1) system conceptualization using the Delphi technique to identify key functionalities that would overcome barriers in provider referrals for smoking cessation, (2) Web system programming and refinement using agile methodology and think-aloud usability testing, (3) implementation planning using the nominal group technique (NGT) for the effective deployment of the system in practices, and (4) pilot testing to identify practice recruitment and system-use barriers .For system conceptualization, we recruited experts  from multiple academic institutions. For usability and pilot testing, we selected practices that would represent the sample in our planned randomized trial. Thus, physicians and nurses from community-based practices across several states in the United States were recruited. For our implementation planning sessions, we recruited physicians from a university setting. Our study was approved by the institutional review boards at the University of Alabama at Birmingham, the Johns Hopkins University School of Medicine, and the University of Massachusetts Medical School.To conceptualize the system, we used a modified Delphi process ,26, a syA panel of 8 experts that included physicians and psychologists with expertise in health services, tobacco control, and informatics participated in the Delphi process. Our goals were to identify the major limitations of current smoking-cessation systems, along with identifying areas to refine in order to maximize physician engagement in the referral of patients to smoking-cessation resources within our system. We conducted three face-to-face discussions over a period of 3 weeks, and in-between email discussions augmented the process. One investigator (TKH) was responsible for synthesizing a literature review and presenting to the panel in the first face-to-face meeting. The same investigator was responsible for summarizing meeting minutes, distributing them by email, and then organizing the email discussions for the next round of the face-to-face discussions in the Delphi process.Agile software development was used to iteratively strategize and plan the programming of the ReferASmoker.org e-referral system. Unlike the traditional approach of specifying system requirements fully at the outset of development and then undertaking programming, the system is developed in units after an overall strategy is formulated. In each agile phase, a short-term goal is set for developing a unit of the system, followed by team development of the unit, including requirements, design, programming, and testing. Agile software development is advantageous because developers can adapt to changing requirements based on the short-term goal setting and collaboration. This approach has also been demonstrated to reduce development time and risk .The ReferASmoker.org Web-based system was programmed using Microsoft’s ASP.NET version 3.5  and C# technology. Microsoft SQL Server version 2000 was used as the database. We used programming best practices in the form of design patterns and modular architecture. Design patterns have been used over the years to solve software development problems. Originally introduced by the Gang of Four , these dmodel that defines the data to be displayed or acted upon in the user interface, (2) a view that displays the model and routes user commands (events) to the presenter, and (3) a presenter that acts upon the model and the view such as formatting the data for display in the view. The modular approach of MVP makes it easier to modify the Web layer without affecting other areas of the system and to unit test the system for programming errors. In addition to the use of MVP in the Web layer, WCSF divides the rest of the system into business modules and foundational modules. Business modules guide the programming of the business logic of the system. The foundational modules are used to program the data access and reusable functions of the system. The modular approach of WCSF makes it easier to make programming changes to the system, as each layer is only loosely connected to the others. This approach also makes it easier to independently test each layer for programming errors using mock data.Frameworks make it easier to use patterns. Specifically, we used the Web Client Software Factory (WCSF) version February 2008 , which iTo implement data access, we used the combination of NHibernate and Castle ActiveRecord frameworks (version Release Candidate 1) ,32. ThesUsability of the system was assessed using the “think-aloud” approach -38. In tThink-aloud interviews were conducted with community providers . A semistructured interview was used to collect input, and optional prompts were used if a provider did not continue to vocalize during the usability interview. The interview was conducted over the phone by study staff trained in the think-aloud protocols. Each interview was recorded and transcribed. Providers were asked to sign onto the ReferASmoker.org system, go through the registration process, and navigate through the site while making comments about their perceptions of the visual layout, as well as the location of options and functions within the system.Once the primary processes were identified, we conducted an NGT session to collect feedback on the referral system and plan for implementation in practices. NGT is a highly structured, multistep, consensus-building procedure often used in formative research to elicit and prioritize group responses to a specific question. It is a consumer-oriented formal brainstorming or idea-generating technique used to foster creativity and to effectively prompt group members to articulate meaningful disclosures ,40. The study was conducted with a panel of experts (n = 9) that included health services researchers, and internal medicine and family practice providers. Using case scenarios, we introduced the goals of the study to the panel, as well as the proposed key components of the Web-based system identified in the process-mapping Delphi. The NGT sessions followed a standard protocol of solicitation of comments, discussion, and ranking of comments by level of importance. Questions posed were as follows: (1) What can we do to help you integrate ReferASmoker into your work clinic?, and (2) What would help you remember to use ReferASmoker?We tested implementation of the system to identify recruitment barriers and areas of refinement in the system. We recruited providers from family practice clinics to participate in the pilot study. Practices in the pilot were representative of participants in our planned larger trial. Using methods from a previously published randomized trial , we mailOnce the practice survey was completed, participants were mailed instructions on how to access and register on the website. We then measured the participant’s usage of the system by tracking their interactions with the website. These data included the pages visited as well as the number of patient referrals on the system. After a period of use, each enrolled practice was contacted by telephone for follow-up; we assessed potential barriers and facilitators to future implementation at that time.We presented results of the literature review to our multidisciplinary research panel with expertise in health services, tobacco control, and informatics. Through the Delphi, our panel identified three key functionalities that would serve to overcome gaps in smoking-cessation referrals in clinical practices. First, the research panel identified the importance of passive referrals such as information prescriptions in cessation efforts . The panp                    roximal                    o                    utcome—a report of the result of screening. These reports  produce a feedback loop and allow for an observable impact. Thus, our panel recommended creating practice reports that detail (1) the number of patients referred, and (2) the number of referred patients actually participating. These rates could be compared with other participating providers and potentially increase referrals.Second, sustained cessation is difficult, and providers do not always have the benefit of observing the positive impact of increased counseling and referral activities. Their attention to smoking cessation has little short-term positive reinforcement. In other referral processes for preventive care, there is often a Third, although many clinic-based interventions refer patients to public health services, such as quitlines, we noted almost no literature on referrals from public health interventions back into clinical care. Recent advances in prescription pharmacotherapy to aid smoking cessation make referral back to the provider for pharmacotherapy even more important. Thus, public health interventions should include content emphasizing the importance of seeking clinical treatment when a patient is ready to quit. The patient website should provide information about how to talk to your doctor about quitting and information about medications. For facilitating linkage back to clinical services, the panel recommended that patient and provider be connected via a secure messaging system. Thus, patients would be supported in the follow-up process, and providers could more easily assist with treatment and arrange follow-up.In summary, based on the findings of the Delphi process, we conceptualized the following: (1) the system should support direct referral at point of care, (2) the system should provide continuous reports on patient activities to encourage continued participation of the providers, and (3) the system should support linkage of patients back to clinical services.Additional functionalities were conceptualized to support the core functionalities noted above, including (1) a “quick-start” guide to train providers to use the system, (2) educational cases and materials to enhance provider knowledge about smoking cessation, (3) downloadable tools to support practice workflow , and (4) methods for engaging providers longitudinally in the system . The ReferASmoker.org Web-based system was programmed using ASP.Net and C# technology . The folThe core Refer Your Smokers function allows providers to proactively refer and enroll patients in the smoking-cessation system during the clinical encounter. To refer a patient, the provider logs into the ReferASmoker.org system and enters a willing patient’s email address. Patients can be referred in multiples or one at a time. The patient referral triggers several automated processes: (1) the patient’s email is entered into the database of the patient online smoking-cessation system, enabling the patient to register and login to the patient system, (2) the system links the patient with the appropriate practice and provider, enabling the practice reports and secure messaging functions, and (3) a series of automated emails is sent to encourage the patient to login to the smoking-cessation system.The practice reports feature was specifically designed to increase observability of provider impact in supporting patients who smoke to take steps to improve their health by quitting . This fuThe secure messaging function was designed to enhance provider–patient communication. Providers can send messages to their patients to encourage use of the patient portal in their smoking-cessation efforts. For convenience, the system provides message templates, but providers have the option to customize them during their registration into the ReferASmoker.org system. A link to the secure messaging function is located within the ReferASmoker.org system so that providers have enhanced communication capabilities with their patients, who also receive this benefit on the portal. Providers can also initiate message threads within the secure messaging system.In addition, we developed a toolbox of educational materials, interactive cases, and news headlines on the website. These materials were developed to supply providers with more general resources and materials to aid in the implementation of smoking-cessation strategies. The interactive cases were followed by questions testing comprehension of the information. Links were embedded in the interactive feedback to redirect the provider to different sections of the education materials to obtain additional information. On completion, providers earned 1 American Medical Association Physician’s Recognition Award category 1 continuing medical education credit for each case. A registration process was created for a provider to register to the system using an email and password combination. The registration process included online consent, a survey, and two customizable email messages to the patient. Once the registration was completed, the provider could login to the system on the home page using the email password combination.Guided by the WCSF, we programmed the system using a modular and flexible architecture. We further divided the modules of the WCSF into the data access layer that enabled structured database access, the service layer that provided a collection of reusable functions, and the business process layer that orchestrated the functionality of system.In the data access layer, using Castle ActiveRecord and NHibernate tools, we created ORM mappings between database tables in the SQL database to C# classes. The ORM mappings also included the relationships that exist between tables in the SQL databases. For example, both a table for the list of providers and another table for the list of practices were developed. A many-to-one relationship exists between these tables . The relationship was replicated in the ORM mappings using the BelongsTo and HasMany attributes of Castle ActiveRecord. The provider class possessed a property indicating that the provider BelongsTo the practice class and the practice class had a property indicating it HasMany providers.In the services layer, we programmed “reusable” data query functions and common utilities that are used throughout the application. The reusable data query functions leverage the data access layer to perform query functions such as select, insert, and update. For example, the system contained provider functions that perform such operations as select all providers belonging to a practice, find the practice of the provider, or find the randomization of a particular practice. The utility functions included methods to send emails and encrypt and decrypt data. A SendEmails function was used throughout the system to send emails to patients, including transmission of secure emails when a provider uses the secure messaging function on the website or transmission of automated emails to encourage registration from the system. The provider and patient identifiers were stored in encrypted form in the database. For this, algorithms to encrypt and decrypt the provider and patients identifiers appropriately were programmed in the DataEncryption function.In the business process layer, we programmed the business logic of the system—that is, a series of tasks that orchestrated the services to realize the functionality of the ReferASmoker.org processes, such as Refer Your Smokers, provider feedback, and secure messaging. For example, the Refer Your Smokers process performed several tasks that need to occur when a provider refers a patient, including (1) determining whether the patient was already referred in the database, (2) if a patient was already in the database, informing the provider that the patient was already referred, and (3) if it was a new patient, adding the patient’s information  and informing the provider that the referral process was successful.Feedback acquired through the think-aloud usability testing was categorized into three themes: (1) registration and login process, (2) general layout, and (3) specific features. As the providers went through the registration process, several issues were identified. First, the instructions indicating that a new user must register and choose a password before using the system were not altogether clear. Second, the providers expressed displeasure with the system automatically assessing the strength of the password provided. Third, instructions for completing the registration survey and particular questions within the instrument were not clearly understood. Finally, the length of the registration process prevented completion of the usability testing process and was seen as a potential barrier to use of the system in practice.Regarding the overall layout of the system, the providers indicated that the website was user-friendly and the various components self-explanatory. Providers expressed particular interest in the news headlines and education components of the system. Providers commented positively on the simplicity and ease of the Refer Your Smokers function. Providers were also pleased that once a referral was made, the system automatically emailed patients to remind them to visit the site. However, concern was expressed regarding the usefulness of the system for patients without email. The practice reports were also believed to be of great utility. Providers remarked that the nationwide comparison of referrals and the real-time activity of their patient panel could serve as motivation to improve. The suggestions for improvement included adding an attention-getting visual to draw the eye to the status column, listing the most active patients at the top of the status report, and adding a mechanism that would announce a patient’s first visit to the website or when a particular patient was doing very well or very poorly.Providers were enthusiastic about the secure messaging function’s potential to engage patients in their own care but provided several thoughts. First, the providers indicated value in the ability to print, download to an electronic medical record, or otherwise archive the messages sent for the medical records. Documenting these communications without additional work was seen as very important for proper follow-up and for possible reuse or modification in the future. Next, providers appreciated both the opportunity to use a preestablished message template that tailored content based on where the patient is in the quit process and the ability to make the messages more personal. Finally, providers commented that it might be beneficial for patients to have the ability to respond to the provider messages to engage them more in their care and in their quit processes, but they also acknowledged that a two-way communication path within the system could prove burdensome for many providers. With regard to the educational toolbox, providers suggested that the various products should be labeled separately for convenience of location on the website. No matter how useful the information, busy clinicians would not spend precious time searching for the information. Further, more information for providers was suggested, including a quick-facts sheet with the latest statistics about smoking and links to the most relevant and recent evidence. Print options for all materials, including other treatment information (for patients), were also suggested. Based on the feedback from the usability results, we made several changes to the system. An easily visible button with the text “NEW USERS! Please click this button to register” was created on the home page to clarify new-user registration instructions. The instructions on the survey page were also clarified. We removed the password strength feature on the username and password creation page. To reduce the additional step of logging in the system after registration, users were redirected to the home page after completing registration. In response to the comments on the practice reports, we created a practice report summary on the home page that contained the following information: (1) a count of the numbers of smokers referred using the system by all practices and the number of smokers referred by the current practice, (2) emails of the last 3 patients of the current practice who were active on the patient site, and (3) the number of smokers of the current practice who have not visited the patient website. We did not create two-way secure messaging between the provider and patient because we felt that this will add additional burden to the providers. To improve the educational materials section, we further classified the materials into three sections: practice forms, interactive cases, and patient education. The first two sections grouped materials for increasing the knowledge and awareness of the provider. The latter sections, though delivered to the provider, contained materials for the provider to use for educating patients. From the NGT session, we identified that several cues to action would be needed to implement ReferASmoker.org in practices, including workflow items and continuous reminders. First, NGT participants emphasized the importance of communicating with the practice through a contact person. This person would serve as the liaison with the practice over a set period of time to inquire about patient recruitment or any other questions or concerns with the system. Second, incentives for participation  were recommended. Third, a continuous communication plan, including both mail and email campaigns, was suggested for ongoing practice engagement. Participants indicated that regular emails would update participants about study progress and provide other information relevant to smoking cessation. Emails with embedded weblinks would provide convenient access back to the system. Fourth, in addressing practice workflow issues, it was recommended that hardcopy materials be sent to the practice to facilitate collection of patient email addresses and website instructions. Finally, NGT participants suggested that successes be appropriately celebrated, perhaps with emails of congratulations and gratitude to practices that logged into the study. In the pilot implementation, 25 practices out of 400 responded to a mailed survey indicating that they were interested in the project, and all of them were mailed a consent form. Of the 25 practices, 8 returned the consent form and were then mailed a practice survey. Of these 8 practices, 7 returned the survey and were given access to the ReferASmoker.org system. Out of those, 6 providers from 5 practices registered with the system, and 5 of them logged into the system. Initially, no providers referred patients. The principal investigator of the study contacted each of the practices by phone to encourage them to use the website. After the call, 1 provider used the referral function to refer 2 patients. Among these, 1 patient visited the patient website. Telephone calls from the principal investigator to enrolled practices were not included in the original pilot implementation and evaluation protocol. However, it became important to elicit information from providers at this stage that could prove helpful in the main trial. We attempted phone contact with all 6 enrolled providers and succeeded in talking with 4. The providers reported barriers and facilitators to practice implementation. Overall, the providers liked the system and thought the intervention was a good idea, but had trouble implementing the system. The staff in the practices constantly changed and newer staff members were unaware of the study. Practices also did not remember whether they had registered with the system. Practices also forgot to e-refer because of lack of visual cues to the intervention. One provider summarized this succinctly, stating “I guess it’s out of sight, out of mind.” Providers encouraged cues to action, with suggestions for a waiting or examination room display that would serve as reminders to refer or to activate patients to talk to them about smoking cessation. Providers were not sure whether the system would be applicable to all patients. All providers agreed that an implementation budget would provide incentives for use of the system.In the preimplementation stage of a nationwide study of an interactive, Web-delivered system to increase provider and patient engagement in smoking cessation, we conducted a rigorous planning and evaluation of the system. The primary purpose of our preimplementation evaluation was to identify the strengths that might be used to promote the program, and weaknesses that might be mitigated prior to initiating the main study. We conceptualized and developed e-referral functions in Web-based form. We report the functions we developed and the results of our usability testing in the Results section. We evaluated the Web system and the implementation plan rigorously with community-based providers. Our approach involved four phases: (1) system conceptualization, (2) agile programming and think-aloud usability testing, (3) implementation planning (using the NGT), and (4) lessons learned from pilot implementation in 7 physician practices. The first barrier was the difficulty contacting the practice and lack of study champion. With no champion identified at each practice, we were constantly speaking with or leaving messages for different staff members, who had little sense of ownership of or urgency in the process. This breakdown in communication was made more complicated with staff turnover, a reality in most medical offices. In order to overcome this particular barrier, we modified the study protocol to include a request for each practice to identify two staff members to serve as implementation coordinators. These implementation coordinators will be the primary contacts for the practice and will work closely with our study personnel. Their responsibility will be to implement and promote the study intervention in the practice. Two implementation coordinators will allow for backup in the event that one individual is unavailable or leaves the practice. Our study personnel will communicate with these implementation coordinators to confirm practice information, hold training sessions, answer any questions, and provide feedback. Second, we identified that successful implementation required training and assistance with registration in the system. Pilot practices reported that the system was easy to use, but with no one trained at the practice to complete the registration process and refer patients and to champion others through the process, the task went undone. Consequently, we increased study personnel and created a proactive helpdesk to provide training and help with registration. In the main study, our staff will initiate contact with each practice within 2 weeks of receiving the returned consent form. Study personnel will verify practice information and schedule a training and registration call for each of the implementation coordinators. During this call, our staff will walk the implementation coordinators through the actual registration process. The study personnel will be on hand to answer any questions. Following registration, study personnel will review the process for referring patients, getting the implementation coordinators to enter a dummy referral to have the full experience of the ease of referral. Each implementation coordinator will be encouraged and provided information to train others in the office to also register and refer patients. Following the training call, study personnel have planned a booster call to verify receipt of printed materials sent and answer any questions that may have arisen in the first few attempts to refer. If no referrals have been made yet, our staff will assess any reasons for no referrals and encourage implementation coordinators to use the system.  The third barrier was a lack of motivation and start-up incentives. It became abundantly clear that motivation to participate was low. We focused on increasing both extrinsic and intrinsic motivation. Pilot data immediately indicated that financial incentives would spur participation. Additional funds from the American Recovery and Reinvestment Act has enabled us to provide honoraria to participating practices and individual staff members who complete training and surveys.Finally, we learned that clinicians within participating practices simply forgot about the study and the need to refer patients through the system. We believe that with convenient reminders we will be able to activate them to use the system. In addition to calling the implementation coordinators to aid them in the registration process and answer any questions, we will increase the work-flow support. We also improved the printed information prescription pads sent to practices for distribution to their patients simultaneously with their online referral. The “Information Rx” that was used in the pilot was small, about the size of a regular prescription pad, and simply provided an optional patient handout. The new and improved pad is spiral bound and has easy check-off boxes with duplicate pages. The bottom half of the first page will be given to the patient. The top half will be returned to study personnel, and the duplicate copy will be ready to place in a patient medical record file. Further, the information prescriptions for the intervention arm have a space for the providers to write the patient’s email address. Additionally, posters to serve as visual stimulation to use the system, posters to encourage patients to talk with their provider about quitting, and 1-page instruction sheets outlining the steps for referring patients will be sent to participating practices.To increase intrinsic motivation and to maximize the brief phone contact with practices, study personnel will incorporate a concept called motivational interviewing into each interaction. Miller and Rollnick define motivational interviewing as a client-centered, directive method for enhancing intrinsic motivation to change by exploring and resolving ambivalence . Key conBecause of our implementation protocol changes, we were successful in engaging practices and improving participation in the nationwide trial. We measured rates of referral and patient participation in the first 3 months of practice engagement. To date, we have analyzed data from the first 50 e-referral practices. Practices’ mean e-referral rate was 14 (SD 13.63). In the first 3 months, the maximum number of referrals by a practice was 62, and 3 practices did not refer. Per practice, the patients mean registration rate was 3.4 (SD 5.09). The maximum number of patients registered with a practice was 28, and 13 practices did not yet have any patients registering.In preparation for a nationwide randomization trial testing an e-referral process for referring patients to a smoking-cessation system by providers, we detail the rigorous steps taken to develop the Web-based e-referral system. At each step of the development process, we applied user input to conceptualize and refine the system. Although the numbers of users are low, the multiple and comprehensive nature of the interactions and data collected provided significant information on which to improve the system’s usability. The results of the mini pilot study gave us critical insight into the recruitment and use barriers that our randomized trial must overcome to succeed.Our how-to report demonstrates how a small, rigorously conducted, multistep preimplementation evaluation can affect the success of a larger study. To gain valuable information regarding potential improvements to an interactive, Web-delivered provider–patient system to increase engagement in smoking cessation, we used a multidimensional approach to conceptualize, develop, implement, and test the product and process. The results of this rigorous process led us to make significant changes to the practice implementation approach study, prior to its nationwide randomized, controlled trial. After refining our information system with usability testing, we further uncovered serious barriers to implementation: lack of study champions within the practice, lack of training and assistance in use of the system, and lack of motivation to participate. We identified several improvements to address and made changes to the main study protocol before trial implementation. Our preliminary analysis with the first 50 practices using the system for 3 months demonstrates the preimplementation evaluation was successful in overcoming the barriers to recruiting and retain study participants.


However, although the strategy described by those authors has been shown to be effective, its usefulness is limited by the fact that the observed effects are only transient. For some research questions, however, it is vital that expression of a specific gene is reduced  for a longer period of time. This article reviews a strategy to ensure long-term expression of another type of interfering RNA molecule—that is, small-hairpin RNAs (shRNAs)—through the use of viral delivery systems . Expression of these shRNAs leads to the destruction of the intermediary molecules  generated during the expression of the target gene.As described in the preceding article by Adams and Zawada . Instead, the shRNA first is artificially inserted  into the genetic material  of a type of virus called lentivirus.In contrast to the genome of most organisms, which consists of DNA, the genome of lentiviruses (and some other viruses) consists of RNA. Once the virus has entered the cell, its genome is converted into DNA that then can integrate into the genome of the host cell. There, the viral genes are expressed, just like the normal cellular genes, using the cell’s own machinery. This ensures sustained expression of the viral genes, including the inserted part encoding the shRNA, thereby allowing for long-term silencing of the gene of interest.196–214.) Various other genes also have been targeted successfully to another brain region called the nucleus accumbens using this vector. Both of these regions play a pivotal role in mediating the rewarding and reinforcing properties of alcohol and other drugs.http://www.dharmacon.com/DesignCenter/DesignCenterPage.aspx) or the siRNA Web site at the Whitehead Institute (available at: http://jura.wi.mit.edu/bioc/siRNAext/). For each gene, three candidate target sequences of 19 nucleotides are chosen. Then, nucleotide chains  are synthesized in the laboratory that contain complementary 19-nucleotide target sequences with the loop sequence inserted between the two complementary sequences (so that they can form the characteristic stem-loop structure of the shRNA) and a signal sequence that stops expression of the shRNA at the right site. Once these oligonucleotides have been introduced into the lentivirus vector, they are first tested in cultured cells to determine if and how effectively they can knock down target gene expression  and purified. It then is injected into the brain region of interest, and knock-down of the target gene can be assessed approximately 2 weeks later see . InitialStudies have found that shRNAs expressed from lentiviral vectors result in sustained knock-down of expression of the gene of interest. This technology can be used to examine the role of a particular gene in specific brain regions and has been useful for studying behaviors related to drugs of abuse, including alcohol.


Hard combinatorial optimization problems deal with the search for the minimum cost solutions (ground states) of discrete systems under strong constraints. A transformation of state variables may enhance computational tractability. It has been argued that these state encodings are to be chosen invertible to retain the original size of the state space. Here we show how redundant non-invertible encodings enhance optimization by enriching the density of low-energy states. In addition, smooth landscapes may be established on encoded state spaces to guide local search dynamics towards the ground state. In particular, the class of NP-complete problems Complex systems in our world are often i.e. non-feasible solutions. For example, the tours of a Traveling Salesman Problem (TSP) The performance of such local search heuristics naturally depends on the structure of the search space, which, in turn, depends on two ingredients: (1) the encoding of the configurations and (2) a move set. Many combinatorial optimization problems as well as their counterparts in statistical physics, such as spin glass models, admit a natural encoding that is  free of redundancy. In the evolutionary computation literature this “direct encoding” is often referred to as the “phenotype space”, neutral if they have the same fitness. Detailed investigations of fitness landscapes arising from molecular biology have led to the conclusion that high degrees of neutrality can facilitate optimization The move set  prepartitioning encoding The so-called The prepartitioning encoding is obtained by modifying the initial condition of the heuristic. Each number reversal. This means that there are indices Our next optimization problem, the Traveling Salesman Problem, (TSP) is another classical NP-hard optimization problem Similar to the NPP case, an encoding configuration Among the tours compatible with the constraint, a selection is made with the greedy algorithm. It constructs a tour by iteratively fixing adjacencies of cities. Starting from an empty set of adjacencies, we attempt to include an adjacency The last example we consider is a Spin Glass problem. Consider the set of configurations The idea for an encoding works on the level of the graph We now study enrichment as well as landscape structure on these three rather different problems. To this end we consider the cumulative density of statesboth to find lower energy states from higher energy ones, and thus have more routes to travel to the ground state, as well as to reach the ground state itself from a low-energy neighbor, as a result of enrichment.Reassuringly, this trend of enrichment persists all the way to the ground state: that is, the encodings contain many more copies of the ground state than the original landscape. It appears in fact that the enrichment of ground states increases exponentially with system size. We can thus conclude that with the choice of an appropriately encoded landscape, it is easier neutral mutation is a small change in the genotype that leaves the phenotype unaltered. In the present setting, a neutral move in the encoding is an edge We continue the analysis of the encodings with attention to geometry and distances. A If a move in the encoding is non-neutral, how far does it take us on the original landscape? We define the step length of a move For the encoding of number partitioning, step lengths are concentrated around One might ask if the encoded landscape also facilitates the search dynamics, by virtue of its modified structure, and offers another avenue for optimization. For this purpose, we consider an optimization dynamics as a zero-temperature Markov chain Adaptive walks also perform strictly better on the encoding than on the original landscape, at least in the long-time limit, cf. viz. the NPP, Spin-Glass and TSP problems, and demonstrated that the choice of a good encoding can indeed help optimization. In the examples we have chosen, the benefits arise primarily as a result of the enrichment of low-energy solutions. A secondary effect in some but not all encodings considered here is the introduction of a high degree of neutrality. The latter enables a diffusion-like mode of search that can be much more efficient than the combination of fast hill-climbing and exponentially rare jumps from local optima. The two criteria, (1) selective enrichment of low energy states and, where possible, (2) increase of local degeneracy, can guide the construction of alternative encodings explicitly making use of a priori knowledge on the mathematical structure of optimization problem. The qualitative understanding of the effect of encodings on landscape structures in particular resolves apparently conflicting “design guidelines” for the construction of evolutionary algorithms.We have examined the role of encodings in arriving at optimal solutions to NP-complete problems: we have constructed encodings for three examples, interpretation as a collection The beneficial effects of enriching encodings immediately pose the question whether there is a generic way in which they can be constructed. The constructions for the NPP and TSP encodings suggest one rather general design principle. Suppose there is a natural way of decomposing a solution complete if A finite discrete energy landscape Random instances fox max-cut (spin glass) are generated as standard random graphs enrichment factorThe The results in The enrichment of the ground state,


Purpose: Cochlear implants (CIs) enable children with severe and profound hearing impairments to perceive the sensation of sound sufficiently to permit oral language acquisition. So far, studies have focused mainly on technological improvements and general outcomes of implantation for speech perception and spoken language development. This study quantitatively explored the organization of the semantic networks of children with CIs in comparison to those of age-matched normal hearing (NH) peers.Method: Twenty seven children with CIs and twenty seven age- and IQ-matched NH children ages 7–10 were tested on a timed animal verbal fluency task . The responses were analyzed using correlation and network methodologies. The structure of the animal category semantic network for both groups were extracted and compared.Results: Children with CIs appeared to have a less-developed semantic network structure compared to age-matched NH peers. The average shortest path length (ASPL) and the network diameter measures were larger for the NH group compared to the CIs group. This difference was consistent for the analysis of networks derived from animal names generated by each group [sample-matched correlation networks (SMCN)] and for the networks derived from the common animal names generated by both groups [word-matched correlation networks (WMCN)].Conclusions: The main difference between the semantic networks of children with CIs and NH lies in the network structure. The semantic network of children with CIs is under-developed compared to the semantic network of the age-matched NH children. We discuss the practical and clinical implications of our findings. Cochlear Implantation (CI) has been the procedure of choice in the last quarter of a century for successful treatment of profound sensorineural hearing loss  and phonological  verbal fluency tasks. To date, there are no other reported studies referring specifically to the semantic level of processing or semantic representations in the CI population  of a randomly chosen node will themselves be neighbors. The ASPL refers to the average shortest amount of steps (nodes being traversed) needed to be taken between any two pair of random nodes. A SWN is characterized by having a large CC and a short ASPL. This model has successfully described a wide range of sociological, technological, biological and economical networks . Two main characteristics of SWNs are the networks clustering coefficient (CC) and its average shortest path length (ASPL). The CC refers to the probability that two neighbors  and switching allows jumping to a new animal subcategory   scarce network research has so far been conducted on this task. This is due to the random nature of both the retrieval exhaustion of subcategories, and the switching process between subcategories. A pioneer research conducted by Goni et al.  developecat, dog, etc., than when retrieving from this subcategory the word dog, it is likely that the word cat will also be retrieved. Thus, we expect a high correlation score between the appearance of the word dog and the appearance of the word cat in our sample—participants who generate the animal word dog, are likely to also generate the animal word cat.The present research introduces a new method to quantitatively analyze the verbal fluency task based on the correlation between word profiles generated by the sample. Our approach takes into account the individual random exhaustion of subcategories, based on subject responses. In this approach, we assume a general organization into subcategories, even if not completely exhausted by an individual subject. For example, if one subcategory of the animal category is household pets, includes In the present study we conduct the first quantitative research on the semantic network of children with CIs, by quantitatively comparing the semantic network of these children with the semantic network of their normal age-matched hearing peers. To this end, we analyzed the results of a verbal fluency task  were included. Seventeen were girls and 10 were boys. Their average TONI score was 109.3 (SD = 10.2). The inclusion criteria for hearing participants were: no parentally reported history of speech or language deficits, no reported neurological or emotional disorders and no known visual impairments that cannot be corrected by glasses. All hearing children underwent an audiological screening before initiating the actual experiments. This screening was conducted at 20 dB in frequencies 500, 1000, 2000, and 4000 Hz. Two responses were required in each frequency in each ear in order to pass the hearing screening.Twenty-seven NH children  were included. Eleven were girls and 16 were boys. Their average TONI score was 109.7 (SD = 11.5). CI participants had severe to profound bilateral sensori-neural hearing loss diagnosed before the age of 3 years, with at least 6 months of experience with CI prior to participation in this study. Nine children used one CI device in one ear only (right or left), 10 had bilateral implants, and 8 had a combination of a CI in one ear and a hearing aid in the other . None of the children included in the analysis had a history of infections or device failure that had caused non-use of the CI for a long period of time. All the children in the CI group were users of oral communication or total communication. The children with CIs were asked to use the typical setting for their CI(s) and hearing aid.Twenty-seven children with CIs  × 132  matrix for the NH group and a 27(subjects) × 106  matrix for the CI group.In order to analyze the data, we converted the responses for each group into data matrices. This matrix was constructed such that each row contains all answers of a single (CI or NH) subject, and each column is a unique animal name given by the entire sample. Each cell, therefore, denotes whether a subject cat and dog), and were calculated by Pearson's formula:The first step in constructing the semantic networks was calculating correlations between the responses to the verbal fluency task. These correlations convey the relation between two word profiles  for all pairs of words define a symmetrical matrix, in which each  element is the correlation between words i and j.Where The word correlation matrix can be studied in terms of an adjacency matrix of a weighted, undirected network. In this approach, each word is a node in the network, and an edge (link) between two nodes (words) is the correlation between them, with the correlation value being the weight of that link. Thus, the word correlation matrix represents a fully connected weighted network in which nodes represent words, and links represent the correlations between words. This representation can be filtered to uncover the most meaningful information about the network. Here we used the Planar Maximally Filtered Graph (PMFG) method to this end . In order to remove any sample size bias, we also added a second analysis, in which we analyzed data from both groups, based on common target animal words given by both groups, by at least two subjects in each group. This resulted in 75 common animal words, generated by both groups. We define these networks as Word-Matched Correlation Networks (WMCN). This process enabled us to quantitatively compare the differences between the networks.S-value larger than 1 (S > 1) defines the network as a SWN.The network parameter calculations (for both SMCNs and WMCNs) were performed with the Brain Connectivity Toolbox for Matlab . The results reveal that the NH-SMCN is more spread out than the CI-SMCN: The NH-SMCN diameter is larger than that of the CI-SMCN (DNH = 16 > DCI = 11); the CC of the NH-SMCN is lower than that of the CI-SMCN, indicating that the CI-SMCN is more condensed than the NH-SMCN (CCNH = 0.66 < CCCI = 0.67) and the ASPL of the NH-SMCN which is larger than that of the CI-SMCN ASPL, indicating that the NH-SMCN is more disperse than the CI-SMCN (LNH = 6.15 > LCI = 4.69). Finally, while the CI-SMCN has fewer nodes than the NH-SMCN (106 nodes vs. 132 nodes), it has a larger small-world-ness score (SNH = 6.57 < SCI = 7.83). This difference in network structure is further evident in a visual presentation of the SMCNs  or by the different words constituting the two networks . In order to eliminate these possible confounds, and in order to compare the semantic networks of both groups, we constructed a WMCN for each group. These WMC networks are comprised of only the common words generated by both groups (75 words). If the semantic networks of both groups are similar, we do not expect any differences in their semantic network statistics.We calculated both WMCNs, in the same method described above. We then calculated the different SWN measures of the WMCNs Table . The resBy calculating the WMC networks that are composed of the same words generated by both groups, we can further examine the difference between the semantic networks of both groups. This was done by three different statistical analyses: first, we generated a large sample of random networks with the same number of nodes and edge probability between nodes as in the WMC networks. This was done to examine whether the network measures calculated for the WMCNs do not result from a null-hypothesis random network. Second, we used the bootstrap method Efron,  to generTo validate the topological properties of the networks, and more important, the topological differences between the NH and CI groups, we use two complementing validation methodologies:Here we examine the statistical measures calculated for both WMC networks, and test that they do not result from a null-hypothesis of a random network. To this end, we generate a large sample of random networks with a fixed edge probability and compare the WMCN topological measures to the values resulting from the bootstrapped simulations.p's < 0.001; Table To conduct this analysis, we first generated an Erdos-Renyi . Thus, while these differences are numerically small, they are significantly different and replicate the main findings—the diameter and the ASPL of the NH network is larger than that of the CI network.In order to conduct our statistical analysis of bootstrapped partial WMC networks, we randomly chose 40 words (nodes) out of the entire 75 words comprising the WMCNs, then constructed for each group separately their partial WMCNs of these random 40 words, and for each such partial WMCN computed their L, D, and CC measures. This process was simulated with 10,000 realizations, and resulted in 10,000 samples of partial WMC networks for groups and their L, D, and CC measures. An independent sample i on the network, defined as the difference between the ASPL of the network after removing node i with the ASPL of the full network.The search for words that have a significant importance in a semantic network can be conducted with network tools. In network theory, the importance of a node is quantified using different measures, such as the betweeness-centrality or the eigenvalues centrality measures  = 13.218; p < 0.01]. As all words in the WMCNs were generated by both groups, this difference indicates a difference in the general structure of the network. This significant difference between the impact scores for all nodes between the two groups further strengthens the findings of the quantitative analysis that indicates a difference in the structure of the network between the two groups.If the networks do not differ, removal of a word In this paper we present the first quantitative examination of the semantic network of children with CIs compared to the semantic network of age-matched NH children. Since research on the semantic aspects of children with CIs is scarce  meanings  influences the spread of activation within the network and to compare these effects between both networks. This examination revealed a significant difference between both networks. If the networks were the same, the removal of a random node Current studies using computational tools to examine the developing brain have revealed a transition in the nature of brain networks, from a SWN to a more ordered, structured nature (Boersma et al., animal semantic category, it would be fruitful to analyze additional semantic categories in order to draw firm conclusions regarding differences in semantic organization of CI and NH children. We plan to further expand our network analysis of the CI children data collected by Wechsler-Kashi et al. (The current study demonstrates the feasibility and importance of applying network tools to examine semantic organization in the CI population. While the results presented here derive only from the i et al. , and to i et al. .In summary, the work presented here is the first quantitative research examining the semantic network of children with CIs. We compared the semantic network of children with CIs to that of age matched NH peers. This comparison allowed us to quantitatively show the difference between these two semantic networks and to describe the nature of this difference. While further work is required in the area of semantics in children with CIs, insights from this and future research might enhance children with CIs semantic processing abilities through therapy, and may shed light on processes related to language acquisition.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.


A non-recurrent variant of the inferior laryngeal nerve has been seldom reported. These reports are mostly based on cadaveric dissection studies or large chart review studies in which the emphasis is placed on the determination of the frequency of the variation, and not on the clinical appearance of this variant. We graphically describe the intraoperative identification of a non-recurrent inferior laryngeal nerve.A 44-year old Caucasian man was referred to the Head and Neck Surgery Outpatient Clinic with the diagnosis of a nodular mass in his left thyroid lobe that had been growing for one year. A fine needle aspiration puncture was compatible with thyroid papillary cancer. It was decided that the patient should undergo total thyroidectomy. During surgery, a non-recurrent right inferior laryngeal nerve was noted. This nerve emanated from the right vagus nerve, entering the larynx 3 cm after its origin. The nerve did not show a recurrent course. The nerve on the left side had a normal configuration. The surgery and post-operative period were uneventful, and the patient had no change in his voice.This paper allows those interested to become acquainted with the normal intraoperative appearance of a non-recurrent inferior laryngeal nerve. This will undoubtedly be of significance for all of those performing invasive diagnostic and surgical procedures in the neck and upper thoracic regions, in order to minimize the risk of iatrogenic injury to this nerve. This is of extreme importance, since a unilateral lesion of this nerve may result in permanent hoarseness, and a bilateral lesion may lead to aphonia and life-threatening dyspnea. From a sensorial point of view, it innervates the mucosal surface of the larynx below the vocal cords . Injury The relatively long course of the inferior laryngeal nerves place them at risk of iatrogenic injury in numerous procedures involving the cervical and upper thoracic regions . Among tA 44-year-old Caucasian man was referred to the Head and Neck Surgery Outpatient Clinic with the diagnosis of a nodular mass in his left thyroid lobe that had been growing since the previous year. His previous medical history was unremarkable. No other enlarged masses or lymph nodes were palpated in the physical examination or detected in the imagiological study of the neck with ultrasound and computed tomography (CT) scan. A fine needle aspiration puncture was performed and the result was compatible with thyroid papillary cancer. In the Group Decision Clinic it was decided that the patient should undergo total thyroidectomy.During surgery, a non-recurrent right inferior laryngeal nerve was noted Figure . This neThe reported incidence of the non-recurrent ILN is widely variable. In some series, the proportion of this variation is null -7 whereaarteria lusoria in which the fourth right aortic arch is abnormally absorbed [dysphagia lusoria) or symptoms related to artery tortuosity, and premature atherosclerosis. Rarely, it is associated with aneurism formation [Despite the discrepancies in the relative proportion of this variant of the ILN, most authors agree that this variant is most common on the right side. The embryological basis for this finding seems to be a vascular disorder known as absorbed . Consequabsorbed ,13,14. Tabsorbed . Even thormation .On the left side, a non-recurrent ILN has only been observed in cases of dextrocardia .arteria lusoria [Theoretically, the pre-operative diagnosis of a non-recurrent ILN could be attempted with imaging studies, namely CT scan or magnetic resonance imaging (MRI), to visualize the  lusoria . However lusoria , it has Invasive procedures in the head and neck region that may compromise the ILN are part of everyday clinical and surgical practice. A sound knowledge of the normal morphology and most frequent variants of the ILN, including its non-recurrent variant, can help doctors to minimize the risk of iatrogenic lesion to this nerve.Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journalThe authors declare that they have no competing interests.All authors have read and approved the final manuscript. DC played a major role in writing the manuscript and analyzed the patient's data. AP aided in the editing of the manuscript and analyzed the patient's data. DS participated in the writing and editing of the manuscript and analyzed the patient's data. JRS aided in the editing of the manuscript and analyzed the patient's data.


The present study reports a case of an extragastrointestinal stromal tumor (EGIST) originating from the seminal vesicles. A 74-year-old male patient with a tumor in the seminal vesicles underwent a radical spermatocystectomy due to an increased defecation frequency and a huge mass in the seminal vesicles. Ultrasonography and computed tomography (CT) initially diagnosed the mass as a tumor originating from the prostate. However, the mass was ultimately confirmed as an EGIST from the seminal vesicles following a laparotomy. According to the size, mitotic activity, cellularity, necrotic situation and immunohistochemical data, the tumor belonged to a low-risk group. No recurrence or metastasis has been identified during six years of follow-up observations. To the best of our knowledge, this is the first study to report this particular pathological type of EGIST. Gastrointestinal stromal tumors (GISTs) are one of the most common types of mesenchymal tumor of the gastrointestinal tract . GISTs were first reported by Mazur and Clark in 1983  are neoplasms with overlapping immunohistological features, occurring in the abdomen outside the gastrointestinal tract with no connection to the gastric or intestinal wall . SimilarA 74-year-old male was admitted to the Second Xiangya Hospital  in October 2005 due to an increased defecation frequency for a duration of more than one year. For one year prior to being admitted, the patient had observed a defecation frequency that had increased from once per day to six-seven times per day without precipitating causes and accompanied by stool reduction. The stool was yellow, but retained its shaped. The patient had no history of a frequent/urgent requirement to urinate, gross hematuria or abdominal pain. The prostate could not be palpated clearly when performing the physical examination, though a huge mass was identified behind the prostate during the rectal examination. The mass was medium-hard without unusual palpable nodules and tenderness. The other physical examinations were normal. Ultrasonography revealed that the boundary of the prostate was unclear and that it was 39×25×23 mm in size. A thick-walled inhomogenous hypoechoic cystic mass (76×77×74 mm), in which the thickness of the cyst wall was uneven, was detected posterior to the prostate. The level of blood prostate specific antigen (PSA) was normal, while the pelvic CT  revealedA laparotomy through an abdomen incision revealed a large, slightly capsulated mass that arose from the seminal vesicle but not the prostate, without connecting to the gastrointestinal tract. The size of the mass was 8×7×7 cm and the capsule boundary was clear, without adherence to the organs around the seminal vesicles. The mass was removed using the no-touch technique. A biopsy and immunophenotype staining were performed. The texture of the mass was moderate and the surface was smooth with a fibrous membrane. Light microscopy examination revealed hemorrhage and necrosis with rich and crowded cells. Karyokinesis was rare and the mitotic index was <10 mitoses per 50 high power fields (HPF). The histopathological diagnosis was of a mesenchymal tumor originating from the seminal vesicle. The immunohistochemical studies revealed that the cells were strongly positive for CD34, CD117, PDGFRA and Vim  and negaGISTs are a type of mesenchymoma and are always located in the GI tract. Generally, the tumors should be classified as EGISTs or GISTs by whether they originate from the GI tract or grow out of the serous membrane. GISTs are characterized by the predominant expression of the c-kit protein and CD34. The combination of the immunohistochemical examinations for c-kit and CD34 are the most reliable markers for the pathological diagnosis of GIST thus far .EGISTs arise from outside the GI tract, but have similar histological features to their GI counterparts, including the morphology, immunophenotype and molecular genetic characteristics. However, the site, growth methods, imaging characteristics and prognosis of EGISTs vary from those of GISTs. In general, EGISTs are an aggressive group of tumors sharing a similarity to GISTs arising in the distal GI tract. EGISTs are rare tumors. From the published literature, it may be observed that the most common EGISTs originate from the omentum, mesentery, retroperitoneum ,12–15 anet al observed that a mitotic rate of >2/50 HPF, the presence of necrosis and a high cellularity was useful in predicting the biological behavior of EGISTs (et al suggested that C-kit gene mutations were not correlated with the prognosis in patients with EGISTs (et al reported the first case of a tumor specimen that contained multiple mutations of c-kit and PDGFRA (Predicting the malignant potential of tumors is significant for their treatment. Mitotic activity, cellularity and the presence of necrosis have been shown to be associated with a worse outcome . A high f EGISTs . Howeverh EGISTs . CD117 ih EGISTs . The PDGd PDGFRA . In the An EGIST of the seminal vesicles must be differentiated from a specific interstitial tumor of the seminal vesicles, including unconfirmed interstitial hyperplasia. The differentiation may be achieved according to the association between the hyperplastic interstitial composition and the body of the seminal vesicles. Immunohistochemical results are the most effective strategy for differentiating between the two types of tumor . NormallThe present case of a stromal tumor in the seminal vesicles may be defined as a GIST-type malignant stromal tumor, rather than a specific interstitial tumor or hyperplasia of the seminal vesicles. This diagnosis was made by the fact that the histological and immunological phenotypes were similar to those of a GIST. The present study may provide clinicians with a reference point for the differential diagnosis of tumors of the prostate and the seminal vesicles.


Methods for storing and sharing biological models tend to focus on directly encoding a model and its equations. However, many models share the same equations, subject only to differences in parameter values or the number of instances of particular processes. We have therefore developed a mechanism within NeuroML to expreThe resulting system, known as LEMS (Low Entropy Model Specification), makes it possible to retro-fit most of the existing NeuroML version 1 definitions with domain independent definitions constructed from LEMS elements. This preserves the benefits of the existing semantically rich high-level concepts in NeuroML while providing the ability to add new concepts at the user level rather than requiring changes to the language. Simulator developers have a choice between directly supporting the library of core types, or supporting the underlying LEMS definitions. These options are not exclusive: a tool could provide hard-coded support for certain key components such as ion channels, and fall back to a generic (and probably less efficient) implementation for new component definitions.Component type definitions in LEMS consist of three main parts: a declaration of the static properties needed to define a particular type of model; specification of the dynamics of the component; and specification of the component's structure. The static definition includes parameters types, component nesting, and references between components. The dynamics contains the equations that govern the behavior of an instance of the model. The structure definition specifies how the static properties should be interpreted when a component is used. This may be as simple as creating a single instance of each of the state variables, but may also involve instantiating other components or connecting them together as in, for example, component types that express network structure or connectivity.As well as an extensive library of component types, and example models, NeuroML2/LEMS contains a reference interpreter that can run any LEMS model. Although initial development has been driven by the need to support the requirements of the NeuroML community, the resulting language only includes mathematical and structural elements and should be applicable to other model specification tasks.


We propose a stochastic segmentation model for parent-specific DNA copy number in tumor samples, and give an estimation procedure that is computationally efficient and can be applied to data from the current high density genotyping platforms. The proposed method does not require matched normal samples, and can estimate the unknown genotypes simultaneously with the parent specific copy number. The new method is used to analyze 223 glioblastoma samples from the Cancer Genome Atlas (TCGA) project, giving a more comprehensive summary of the copy number events in these samples. Detailed case studies on these samples reveal the additional insights that can be gained from an allele-specific copy number analysis, such as the quantification of fractional gains and losses, the identification of copy neutral loss of heterozygosity, and the characterization of regions of simultaneous changes of both inherited chromosomes.Chromosomal gains and losses comprise an important type of genetic change in tumors, and can now be assayed using microarray hybridization-based experiments. Most current statistical models for DNA copy number estimate total copy number, which do not distinguish between the underlying quantities of the two inherited chromosomes. This latter information, sometimes called  Many genetic diseases are related to copy number aberrations of some regions of the genome. As we know, each chromosome normally has two copies. However, under some circumstances, for some regions, either one or both of the chromosomes change. Genotyping microarray data provides the copy number of the two alleles of polymorphic sites along the chromosomes, which make the inference of the copy number aberrations of the chromosome feasible. One difficulty is that genotyping microarray data cannot provide the haplotype of the two copies of a chromosome. In this paper, we model the copy number along the chromosome as a two-dimensional Markov Chain. Using the observed copy number of both alleles of all the sites, we can determine the parent specific copy number along the chromosome as well as infer the haplotypes of the two copies of the inherited chromosomes in regions where there is allelic imbalance. Simulation results show high sensitivity and specificity of the method. Applying this method to glioblastoma samples from the Cancer Genome Atlas data illustrate the insights gained from allele-specific copy number analysis. Various microarray based experimental platforms This paper addresses the problem of parent specific copy number estimation using allele-specific raw copy number data from high-density genotyping arrays. We will describe the data in more detail in the next section. Here, we clarify the differences between total copy number analysis and parent specific copy number analysis, and review the background of the computational treatment of this problem.The genome of each somatic human cell normally contains two copies of each of the 22 autosomes, one inherited from each biological parent. At any genome location, one or both of these two chromosomes may gain or lose copies, thus creating a change in total copy number at that location. Microarray experiments for measuring total copy number produce a sequence of continuous valued measurements mapping to ordered locations along the chromosomes. Computational methods can be applied to segment this noisy sequence of measurements into regions of homogeneous copy number Total copy number estimates do not reveal which (or both) of the two inherited chromosomes have been gained or lost, and if a locus is polymorphic, which (or both) of the alleles have been affected. This information is now available in data produced by high density genotyping platforms, which give, at selected single nucleotide polymorphisms (SNPs), a bivariate measurement quantifying the two alleles which we arbitrarily label This problem can be formulated statistically as follows: The observed There have been much effort extending existing genotyping and total copy number segmentation procedures to analyze allele-specific data. At the probe level, CNAT The fractional changes in tumors inspired recent approaches In light of these recent developments, we need a systematic stochastic model for parent specific copy number which can accommodate fractional copy number changes. We propose a general two-chromosome hidden Markov model for this problem. The hidden states of the model represent the copy numbers of each of the two inherited chromosomes, and take value in the continuous space of real numbers. Thus, unlike discrete state space HMMs, this model is not limited to idealized unit-copy changes. Computationally efficient fitting algorithms are given that scale well to data obtained from the current high density genotyping arrays. The estimation procedure based on the two chromosome model, which we call Parent-Specific-Copy-Number (PSCN), extends the framework developed in Lai et al. After segmenting the genome into regions of constant parent-specific copy number, we identify, for each region, whether both or only one of the parental chromosomes have changed copies. We also determine, in regions containing simultaneous gain of one chromosome and loss of the other, whether the changes are balanced. Thus, we classify the regions into six different types of aberrations depending on the status of the two parental chromosomes: gain of both chromosomes (gain/gain), gain of only one chromosome , gain of one chromosome and balanced loss of the other chromosome , gain of one chromosome and unbalanced loss of the other chromosome , loss of only one chromosome  and loss of both chromosomes (loss/loss). To our knowledge, this is the most detailed classification available among methods for allele-specific analysis. The PSCN method outputs the copy number for both chromosomes in each segment.We evaluate the accuracy of the proposed procedure on a series of simulated tumor titration data provided by Staaf et al. parent-specific, we distinguish between the chromosomes inherited from the two parents, which we treat as exchangeable and do not label as maternal or paternal. Let Let observed allele specific signals Note that when a somatic event causes a change in copy number of one or both parental chromosomes at SNP normal state , where variant state, where same variant state with probability different variant state with probability To model the gains and losses of the two inherited chromosomes, we assume that We assume that the inherited allele configurations Note that this model contains many assumptions, including Gaussianity of the allele specific intensities and Markovicity of the underlying copy number states. These assumptions allow fast and explicit analytic formulas to be derived, thus avoiding the need for Monte Carlo based estimates. For most platforms, the allele-specific intensities deviate from Gaussianity, despite careful normalization. Also, there has never been proof that chromosomal breakages are Markovian. These assumptions are made for modeling convenience, just as in the total-copy number estimation problem Our primary objective is to estimate the parent specific copy numbers Fix stopping threshold Expectation step: Given Maximization step: Given If In each iteration of the above algorithm, the expectation step estimates The above algorithm returns a soft segmentation of The segmentation divides the genome into regions where the copy numbers of the two inherited chromosomes are constant. It is often useful to know, for each region, whether the copy numbers of one or both parental chromosomes deviate from the normal level. This involves classifying each region into one of the following six types of chromosomal change: gain/gain, gain/normal, balanced gain/loss, unbalanced gain/loss, normal/loss and loss/loss.For each segmented region, we define the major copy number to be the normalized raw copy number of the more abundant chromosome, and the minor copy number to be the normalized raw copy number of the less abundant chromosome. If the two chromosomes have equal copy numbers, then the major and minor chromosome labels are assigned arbitrarily. The major and minor copy numbers are estimated after the hard-segmentation using a mixture model on the heterozygous SNPs in each region . The color scheme of the mm-plot reflects the gain/loss status of each region, where red represents gain, blue represents loss, and green represents normal. It is usually difficult to discern the relative magnitudes of gains and losses from the We now zoom in on two example regions to illustrate the additional insights gained from parent-specific copy number analysis. These regions are shown in First, consider the example region from TCGA sample 02-0332 on the left panel. There are three instances of copy neutral LOH, colored in purple. Based on the BAF plot, the loss seems to be complete, that is, it is carried by almost all of the cells in the sample. The Following the copy neutral LOH regions in chromosome 3 of sample 02-0332, there is a stretch of alternating gains and losses, colored respectively in red and blue. The copy of the other parental chromosome in these regions is one. As seen from the The same reasoning can be applied to the red and pink regions of chromosome 2 of TCGA sample 02-0258 (right panel), which contains a fractional gain. By teasing apart the copy numbers of each inherited chromosome, we are now able to characterize and quantify these fractional changes.Now consider the example region color coded in purple from TCGA sample 02-0258 in the right panel. The We have developed a method for simultaneous estimation of parent-specific DNA copy number and inherited genotypes for tumor samples using allele-specific raw copy number data. The model and estimation procedure start with transforming allele-specific data into ion file . We illuA rigorous assessment using in silico titration data provided by Staaf et al. PSCN is not platform specific, and we have also applied it to data from the Affymetrix Genotyping 6.0 array, with an example analysis given in the Supporting Information file . The segAn overview of an analysis of the TCGA glioblastoma samples reveal that a substantial fraction of copy number changes are copy-neutral loss of heterozygosity events. These events would not have been found using analyses based only on total copy number. Cases of unbalanced simultaneous changes in the copy numbers of both inherited chromosomes were also found. It would be of interest to quantify the frequency of such changes among different cancer subtypes and in other types of tumors.A final point that we would like to emphasize is the quantification of fractional changes, as exemplified by the two case studies on the TCGA glioblastoma samples. Since this requires teasing apart the quantities of the two inherited chromosomes, it can only be achieved through allele-specific estimates. The fraction of cells that carry each copy number event is important for downstream analyses, such as quantifying normal cell contamination and studying tumor microevolution. The parent-specific copy number estimates obtained from the proposed method provides a starting point for these types of investigations.http://r-forge.r-project.org/) under project name PSCN.The R package for PSCN is registered on R-Forge . Let Let Since The variables Let Step 1: Initialize: Step 2: SetStep 3: SetStep 4: Stop if The motivation of the initial and default settings are as follows. For segment with changed states, the goal is to estimate minor and major copy number. It is expected that the minor copy number would be less than or equal to 1 and the major copy number would be larger than or equal to 1, so the initial values for Denote the estimated parameters by Text S1Supporting materials for PSCN.(0.28 MB PDF)Click here for additional data file.