Final presentation

Here is some of the information on my final poresentation with the apropriate source sightings. I will email you my powerpoint. A program for performing differential diagnosis on a microcomputer has been developed, utilizing a pattern recognition algorithm. The present configuration allows for input of 15 symptoms of 3 values (present, absent, or unknown), and compares the patient's symptom profile with 50 patterns which point to as many as 10 disease designations. The investigator may stipulate either a rigorous or permissive pattern matching, thus obtaining either a selective or exhaustive ranking of possible diagnoses. The program can record patient data, recall data given any one parameter, and can construct tables of incidence. This inexpensive system was designed for an office or community level practice, where the pattern arrays will be trained for its specific patient populations. Presently, data from the Georgetown University Student Health Service is being introduced as the program's first clinical trial. Background: Clinical decision support systems assist physicians in interpreting complex patient data. However, they typically operate on a per-patient basis and do not exploit the extensive latent medical knowledge in electronic health records (EHRs). The emergence of large EHR systems offers the opportunity to integrate population information actively into these tools. Methods: Here, we assess the ability of a large corpus of electronic records to predict individual discharge diagnoses. We present a method that exploits similarities between patients along multiple dimensions to predict the eventual discharge diagnoses. Results: Using demographic, initial blood and electrocardiography measurements, as well as medical history of hospitalized patients from two independent hospitals, we obtained high performance in cross-validation (area under the curve >0.88) and correctly predicted at least one diagnosis among the top ten predictions for more than 84% of the patients tested. Importantly, our method provides accurate predictions (>0.86 precision in cross validation) for major disease categories, including infectious and parasitic diseases, endocrine and metabolic diseases and diseases of the circulatory systems. Our performance applies to both chronic and acute diagnoses. Conclusions: Our results suggest that one can harness the wealth of population-based information embedded in electronic health records for patient-specific predictive tasks. [ABSTRACT FROM AUTHOR] This paper examines the diagnostic storytelling that medical residents perform in order to situate patients in a story trajectory with an imputed past and future. It is a study of “ordinary” expertise, as practiced by a family practice medical team in a small urban community hospital in the United States. Narrative storytelling—an activity that is at once cognitive and practical—allows residents to identify the sort of disease, the kind of patient, and the likely outcome for this patient, based on what the resident knows about patients like these. Residents acquire a set of narrative templates, or rough outlines, that they deploy when they encounter a new patient or his or her information. Going into an admissions interview, a resident already has a set of “facts” about the patient and his or her complaint. In a process that is routine, habitual, and iterative, a resident starts from this set of facts and draws on his or her repertoire of narrative templates to pursue a line of questioning that starts to define relevance for this patient, a relevance that is revised as the physician begins to settle on a story. These templates make a first organizing pass at answering, “What’s going on with this patient?” They provide the preliminary structure, the warp and weft, for building a patient story that holds together long enough to diagnose, treat, and discharge the patient. Diagnostic stories are shaped by what residents think they can do for the patient, practically speaking, and by habitual hospital activity. Most current model-based diagnosis formalisms and algorithms are defined only for static systems, which is often inadequate for medical reasoning. In this paper we describe a model-based framework plus algorithms for diagnosing time-dependent systems where we can define qualitative temporal scenarios. Complex temporal behavior is described within a logical framework extended by qualitative temporal constraints. Abstract observations aggregate from observations at time points to assumptions over time intervals. These concepts provide a very natural representation and make diagnosis independent of the number of actual observations and the temporal resolution. The concept of abstract temporal diagnosis captures in a natural way the kind of indefinite temporal knowledge which is frequently available in medical diagnoses. We use viral hepatitis B (including a set of real hepatitis B data) to illustrate and evaluate our framework. The comparison of our results with the results of Hepaxpert-I is promising. The diagnosis computed in our system is often more precise than the diagnosis in Hepaxpert-I and we detect inconsistent data sequences which cannot be detected in the latter system. Background: Deriving an appropriate differential diagnosis is a key clinical competency, but there is little data available on how medical students learn this skill. Software resources designed to complement clinical reasoning might be asset in helping them in this task. Aims: The goals of this study were to identify the resources third year medical students use to solve a challenging diagnostic case, and specifically to evaluate the usefulness of Isabel, a second-generation electronic diagnosis support system. Methods: Third year medical students (n = 117) were presented a challenging case and asked to identify and prioritize their top 3 diagnoses, report the time devoted to the exercise, and list the resources they used and their relative usefulness. Students were randomized to receive (or not) free access, instruction, and encouragement to use to a web-based decision support system (Isabel). Results: Students who identified the correct diagnosis as their first choice spent significantly more time on the case than did the other students (3.75 ± 0.28 hours vs 2.88 ± 0.15 hours, p < 0.05). Students used electronic resources extensively, in particular Google. Students who self-reported use of Isabel had greater success identifying the correct diagnosis (24/33 = 73% for users vs 45/84 = 53% for non-users) a difference of borderline statistical significance. Conclusions: These findings indicate that medical trainees use a wide range of electronic decision support products to solve challenging cases. Medical education needs to adapt to this reality, and address the need to teach future clinicians how to use these tools to advantage. [ABSTRACT FROM AUTHOR] Time per visit Objectives. To use an innovative videotape analysis method to examine how clinic time was spent during elderly patients' visits to primary care physicians. Secondary objectives were to identify the factors that influence time allocations. Data Sources. A convenience sample of 392 videotapes of routine office visits conducted between 1998 and 2000 from multiple primary care practices in the United States, supplemented by patient and physician surveys. Research Design. Videotaped visits were examined for visit length and time devoted to specific topics—a novel approach to study time allocation. A survival analysis model analyzed the effects of patient, physician, and physician practice setting on how clinic time was spent. Principal Findings. Very limited amount of time was dedicated to specific topics in office visits. The median visit length was 15.7 minutes covering a median of six topics. About 5 minutes were spent on the longest topic whereas the remaining topics each received 1.1 minutes. While time spent by patient and physician on a topic responded to many factors, length of the visit overall varied little even when contents of visits varied widely. Macro factors associated with each site had more influence on visit and topic length than the nature of the problem patients presented. Conclusions. Many topics compete for visit time, resulting in small amount of time being spent on each topic. A highly regimented schedule might interfere with having sufficient time for patients with complex or multiple problems. Efforts to improve the quality of care need to recognize the time pressure on both patients and physicians, the effects of financial incentives, and the time costs of improving patient–physician interactions. [ABSTRACT FROM AUTHOR] The objectives of this study were to assess the relationship between wait time and parent satisfaction and determine whether time with the physician potentially moderated any observed negative effects of long wait time. Data were collected from parents in a pediatric outpatient clinic. Parent satisfaction with the clinic visit was significantly negatively related to wait times. More time spent with the physician was positively related to satisfaction independent of wait times. Furthermore, among clinic visits with long wait times, more time with the physician showed a relatively strong positive relationship with parent satisfaction. Therefore, although long wait times was related to decreased parent satisfaction with pediatric clinic visits, increased time with the physician tended to moderate this relationship. This paper reports a study exploring patients' views about consulting with a primary care nurse practitioner. United Kingdom based randomized controlled trials comparing the work of doctors and nurse practitioners add considerable weight to the view that patients tend to be more satisfied with primary care nurse practitioner consultations. However, there is a need for qualitative research to explore issues raised by the trials. A judgement sample of 10 patients consulting with a primary care nurse practitioner was drawn. In-depth interviews were conducted and analysed thematically. The data were collected in 2000-2001. The following themes were identified in the data: time spent in the consultation; and time as a commodity in patients' lives. Time matters to patients when they consult on their health, whether it is time to discuss problems or time saved as a result of having issues resolved, thus minimizing further visits. Factors associated with the style and emphasis of consultations are also important. Understanding the relationship between time, and style and emphasis of consultation may help to explain patients' satisfaction with primary care nurse practitioners. Question: Why Do I Wait In the Waiting Room for Such a Long Time at a Doctors Appointment? Patients are often frustrated that they make an appointment for a certain time, they arrive on time, yet they are kept in the waiting room for too long a time before they see the doctor. When we understand why this happens, we can take steps to change it, or make it easier to tolerate. Answer: Like too many questions in healthcare, the answer to why we are kept in the waiting room for so long is, "follow the money." Doctors are paid by insurance and Medicare for every patient they see according to why they see the patient, and what procedures they perform for the patient, and (this is key) not by the amount of time they spend with the patient. Since their goal is to maximize their income, they will schedule as many patients into their day as possible. More patients plus more procedures equals more income. In any given day, they may not be sure what services they'll be performing for individual patients, and some patients require more time for their services than others. Equipment may break down. An obstetrician may be delivering a baby. There may even be emergencies. We lose our patience because we believe the time just has not been scheduled well. Understanding that it's the volume of patients and procedures, not the time spent per patient, that comprises a doctors' income, it's easier to understand why they get so far behind, and why we are kept waiting. Nationwide, the average wait time to see a doctor last year was 23 minutes, according to the health care consultants Press Ganey. Neurosurgeons have the longest wait times (30 minutes) and optometrists the shortest (17 minutes), according to the report. Fisher, Paul. "Micro Computers in Medical Diagnosis." ACM Digital Library. 01 01 1980: 75-79. Web. 13 Dec. 2013. . (Fisher 75-79) Davenport, Nancy. "Medical residents’ use of narrative templates in storytelling and diagnosis." Social Science & Medicine. 01 09 2011: 1. Web. 13 Dec. 2013. (Davenport 1) Johann, Christopher. "Abstract temporal diagnosis in medical domains." Artificial Intellegence in Medicine. 01 07 1997: 1. Web. 13 Dec. 2013. . (Johann 1) Feddock, Christopher. "Is Time Spent With the Physician Associated With Parent Dissatisfaction Due to Long Waiting Times?." Evaluation & The HEalth Profession. 10 05 2010: 1. Web. 13 Dec. 2013. . (Feddock 1) Torrey, Trisha. "Why Do I Wait In the Waiting Room for Such a Long Time at a Doctors Appointment?." Patient Empowerment. 14 11 2008: 1. Web. 13 Dec. 2013. . (Torrey 1) Alderman, Lesley. "The Doctor Will See You Eventually." New York Times. 01 08 2011: 1. Web. 13 Dec. 2013. . (Alderman 1)

Diagnostics

Here is some of the research that I have conducted. I have made a power point that I do not know how to load to this blog, but I am presenting on diagnostics in the doctors office, how this can be improved, how time can be saved, and correct diagnosis can be made effectively nd efficiantly.I am a Human comm and Chemistry major and this presentation addresses both of these areas. A program for performing differential diagnosis on a microcomputer has been developed, utilizing a pattern recognition algorithm. The present configuration allows for input of 15 symptoms of 3 values (present, absent, or unknown), and compares the patient's symptom profile with 50 patterns which point to as many as 10 disease designations. The investigator may stipulate either a rigorous or permissive pattern matching, thus obtaining either a selective or exhaustive ranking of possible diagnoses. The program can record patient data, recall data given any one parameter, and can construct tables of incidence. This inexpensive system was designed for an office or community level practice, where the pattern arrays will be trained for its specific patient populations. Presently, data from the Georgetown University Student Health Service is being introduced as the program's first clinical trial. Background: Clinical decision support systems assist physicians in interpreting complex patient data. However, they typically operate on a per-patient basis and do not exploit the extensive latent medical knowledge in electronic health records (EHRs). The emergence of large EHR systems offers the opportunity to integrate population information actively into these tools. Methods: Here, we assess the ability of a large corpus of electronic records to predict individual discharge diagnoses. We present a method that exploits similarities between patients along multiple dimensions to predict the eventual discharge diagnoses. Results: Using demographic, initial blood and electrocardiography measurements, as well as medical history of hospitalized patients from two independent hospitals, we obtained high performance in cross-validation (area under the curve >0.88) and correctly predicted at least one diagnosis among the top ten predictions for more than 84% of the patients tested. Importantly, our method provides accurate predictions (>0.86 precision in cross validation) for major disease categories, including infectious and parasitic diseases, endocrine and metabolic diseases and diseases of the circulatory systems. Our performance applies to both chronic and acute diagnoses. Conclusions: Our results suggest that one can harness the wealth of population-based information embedded in electronic health records for patient-specific predictive tasks. [ABSTRACT FROM AUTHOR] This paper examines the diagnostic storytelling that medical residents perform in order to situate patients in a story trajectory with an imputed past and future. It is a study of “ordinary” expertise, as practiced by a family practice medical team in a small urban community hospital in the United States. Narrative storytelling—an activity that is at once cognitive and practical—allows residents to identify the sort of disease, the kind of patient, and the likely outcome for this patient, based on what the resident knows about patients like these. Residents acquire a set of narrative templates, or rough outlines, that they deploy when they encounter a new patient or his or her information. Going into an admissions interview, a resident already has a set of “facts” about the patient and his or her complaint. In a process that is routine, habitual, and iterative, a resident starts from this set of facts and draws on his or her repertoire of narrative templates to pursue a line of questioning that starts to define relevance for this patient, a relevance that is revised as the physician begins to settle on a story. These templates make a first organizing pass at answering, “What’s going on with this patient?” They provide the preliminary structure, the warp and weft, for building a patient story that holds together long enough to diagnose, treat, and discharge the patient. Diagnostic stories are shaped by what residents think they can do for the patient, practically speaking, and by habitual hospital activity. Most current model-based diagnosis formalisms and algorithms are defined only for static systems, which is often inadequate for medical reasoning. In this paper we describe a model-based framework plus algorithms for diagnosing time-dependent systems where we can define qualitative temporal scenarios. Complex temporal behavior is described within a logical framework extended by qualitative temporal constraints. Abstract observations aggregate from observations at time points to assumptions over time intervals. These concepts provide a very natural representation and make diagnosis independent of the number of actual observations and the temporal resolution. The concept of abstract temporal diagnosis captures in a natural way the kind of indefinite temporal knowledge which is frequently available in medical diagnoses. We use viral hepatitis B (including a set of real hepatitis B data) to illustrate and evaluate our framework. The comparison of our results with the results of Hepaxpert-I is promising. The diagnosis computed in our system is often more precise than the diagnosis in Hepaxpert-I and we detect inconsistent data sequences which cannot be detected in the latter system. Background: Deriving an appropriate differential diagnosis is a key clinical competency, but there is little data available on how medical students learn this skill. Software resources designed to complement clinical reasoning might be asset in helping them in this task. Aims: The goals of this study were to identify the resources third year medical students use to solve a challenging diagnostic case, and specifically to evaluate the usefulness of Isabel, a second-generation electronic diagnosis support system. Methods: Third year medical students (n = 117) were presented a challenging case and asked to identify and prioritize their top 3 diagnoses, report the time devoted to the exercise, and list the resources they used and their relative usefulness. Students were randomized to receive (or not) free access, instruction, and encouragement to use to a web-based decision support system (Isabel). Results: Students who identified the correct diagnosis as their first choice spent significantly more time on the case than did the other students (3.75 ± 0.28 hours vs 2.88 ± 0.15 hours, p < 0.05). Students used electronic resources extensively, in particular Google. Students who self-reported use of Isabel had greater success identifying the correct diagnosis (24/33 = 73% for users vs 45/84 = 53% for non-users) a difference of borderline statistical significance. Conclusions: These findings indicate that medical trainees use a wide range of electronic decision support products to solve challenging cases. Medical education needs to adapt to this reality, and address the need to teach future clinicians how to use these tools to advantage. [ABSTRACT FROM AUTHOR] Time per visit Objectives. To use an innovative videotape analysis method to examine how clinic time was spent during elderly patients' visits to primary care physicians. Secondary objectives were to identify the factors that influence time allocations. Data Sources. A convenience sample of 392 videotapes of routine office visits conducted between 1998 and 2000 from multiple primary care practices in the United States, supplemented by patient and physician surveys. Research Design. Videotaped visits were examined for visit length and time devoted to specific topics—a novel approach to study time allocation. A survival analysis model analyzed the effects of patient, physician, and physician practice setting on how clinic time was spent. Principal Findings. Very limited amount of time was dedicated to specific topics in office visits. The median visit length was 15.7 minutes covering a median of six topics. About 5 minutes were spent on the longest topic whereas the remaining topics each received 1.1 minutes. While time spent by patient and physician on a topic responded to many factors, length of the visit overall varied little even when contents of visits varied widely. Macro factors associated with each site had more influence on visit and topic length than the nature of the problem patients presented. Conclusions. Many topics compete for visit time, resulting in small amount of time being spent on each topic. A highly regimented schedule might interfere with having sufficient time for patients with complex or multiple problems. Efforts to improve the quality of care need to recognize the time pressure on both patients and physicians, the effects of financial incentives, and the time costs of improving patient–physician interactions. [ABSTRACT FROM AUTHOR] The objectives of this study were to assess the relationship between wait time and parent satisfaction and determine whether time with the physician potentially moderated any observed negative effects of long wait time. Data were collected from parents in a pediatric outpatient clinic. Parent satisfaction with the clinic visit was significantly negatively related to wait times. More time spent with the physician was positively related to satisfaction independent of wait times. Furthermore, among clinic visits with long wait times, more time with the physician showed a relatively strong positive relationship with parent satisfaction. Therefore, although long wait times was related to decreased parent satisfaction with pediatric clinic visits, increased time with the physician tended to moderate this relationship. This paper reports a study exploring patients' views about consulting with a primary care nurse practitioner. United Kingdom based randomized controlled trials comparing the work of doctors and nurse practitioners add considerable weight to the view that patients tend to be more satisfied with primary care nurse practitioner consultations. However, there is a need for qualitative research to explore issues raised by the trials. A judgement sample of 10 patients consulting with a primary care nurse practitioner was drawn. In-depth interviews were conducted and analysed thematically. The data were collected in 2000-2001. The following themes were identified in the data: time spent in the consultation; and time as a commodity in patients' lives. Time matters to patients when they consult on their health, whether it is time to discuss problems or time saved as a result of having issues resolved, thus minimizing further visits. Factors associated with the style and emphasis of consultations are also important. Understanding the relationship between time, and style and emphasis of consultation may help to explain patients' satisfaction with primary care nurse practitioners. Question: Why Do I Wait In the Waiting Room for Such a Long Time at a Doctors Appointment? Patients are often frustrated that they make an appointment for a certain time, they arrive on time, yet they are kept in the waiting room for too long a time before they see the doctor. When we understand why this happens, we can take steps to change it, or make it easier to tolerate. Answer: Like too many questions in healthcare, the answer to why we are kept in the waiting room for so long is, "follow the money." Doctors are paid by insurance and Medicare for every patient they see according to why they see the patient, and what procedures they perform for the patient, and (this is key) not by the amount of time they spend with the patient. Since their goal is to maximize their income, they will schedule as many patients into their day as possible. More patients plus more procedures equals more income. In any given day, they may not be sure what services they'll be performing for individual patients, and some patients require more time for their services than others. Equipment may break down. An obstetrician may be delivering a baby. There may even be emergencies. We lose our patience because we believe the time just has not been scheduled well. Understanding that it's the volume of patients and procedures, not the time spent per patient, that comprises a doctors' income, it's easier to understand why they get so far behind, and why we are kept waiting. Nationwide, the average wait time to see a doctor last year was 23 minutes, according to the health care consultants Press Ganey. Neurosurgeons have the longest wait times (30 minutes) and optometrists the shortest (17 minutes), according to the report. http://dl.acm.org.libproxy.dixie.edu/citation.cfm?id=809930 Ebsco Host AN 90652516 http://www.sciencedirect.com.libproxy.dixie.edu/science/article/pii/S0277953611001201 http://www.sciencedirect.com.libproxy.dixie.edu/science/article/pii/S093336579700393X EBSCO HOST AN 42869273 EBSCO HOST AN 26518045 http://ehp.sagepub.com.libproxy.dixie.edu/content/33/2/216 EBSCO HOST AN 2009124550 http://patients.about.com/od/followthemoney/f/FAQappointments.htm http://www.nytimes.com/2011/08/02/health/policy/02consumer.html?_r=0 Taxes, ball game, plain flight, tee time…………what about a doctors visit?

The Future of Story

Pretty funny the way that Paul Bellini explains so colorfully that story telling is dead. In his article “The Death of Story Telling” he explains that, “We don’t go to the movies to see stories anymore. We go to watch shit blow up. And all we leave the theatre with is shit. Is storytelling dead? Bellini goes on to give ten reasons as to why story telling is dying if not dead. His argument is that the plots of movies in particular are mostly generic. You have a super hero that will in the end defeat the villain. He uses the examples that ghosts are able to move things and can be seen by those that are living. “What is more finite than death?” Bellini believes that television networks are to blame for the downfall of story telling. Gottschall on the other hand has a much grander view and much more optimistic view of the future of story telling. Gottschall sees poetry in the genres of the music that is most popular in today’s societies. Rap and R&B give poetry a new image, an image that is cool, hip, and cutting edge. “Ours is not the age when poetry died; it is the age when poetry triumphed in the form of song.” Gottschall also uses the example of WoW, Call of Duty, and Modern Warfare 3 to explain that story is alive and well in todays youth. It is my opinion that you can take the side of ether of these two men. It would depend on how you define story telling; if you look at the play writes such as Shakespeare, it is my opinion that his brilliance has not been matched, but also that brilliance has not been lost. Take the mind of Spielberg and others who have brought us Star Wars and Avatar. It is my opinion that these are great stories told by brilliant minds. http://gutterbird.com/secrets/?p=1134

The Future of Story

The question is asked is it possible to write a genuinely honest memoir or autobiography? I would say ABSOLUTLY! Here is the thing, do you want it to be entertaining, exciting, and something that everyone would like to read? Most of our lives are mundane and boring. Yes there are exciting times, sad times, times when we are falling in love and falling out of love but those experiences are so short and they seems to be so much time that passes from one exciting moment to the next that in most cases our lives would not be entertaining to others. As human race we have all had the opportunity to experience lose, heartbreak, love, and triumph at one time or another depending on your age. All these experiences draw us together and allow us to have something in common with others. Rather than being sympathetic to someone’s plight, we can be empathetic and understanding because we have experienced these feelings ourselves which gives us the opportunity to feel accepted or to feel that we can contribute to others. It is interesting in this chapter how often Gottschell says “I”. He expresses more frequently in this chapter how he feels the future of story telling will be. Saying things like “we will be doing so in cyber space, not the real world.” Gottschell talks about the introduction of “feelies.” What a scary idea, here you can not only “watch porn” but “feel the smashing lips” scary thought! Gottschell believes that the future will be much like the helm of the “Star Trek Enterprise” it is scary to think that with the technology advancements that we as a species would lose one another, lose the ability to communicate, lose the ability to interact with one another, lose the ability to have sex with one another because we can now experience these things through cyber space! SCARY! We all use our imaginations from childhood into adolescences and into our adult lives. It is my opinion that it is a survival mechanism and that without it we will lose ourselves. Children are encouraged to make believe, to develop their minds and bodies, preparing them for their future. I don’t believe that story telling is going anywhere, but I am concerned with the development of video games, the cyber world, and were these realms may take us. I have decided to go the route of stem cells and the opportunity this research gives the human race. I have used the resources through summon and have come up with these three sources to start. http://www.sciencedirect.com.libproxy.dixie.edu/science/article/pii/S0167779903000039 http://www.sciencedirect.com.libproxy.dixie.edu/science/article/pii/S1526054206000297 STEM CELL RESEARCH; Choice of method for derivation of ESCs depends on the quality of the blastocyte

Tenth Blog Response

Talks about rice and iron deficiency in Africa. It is interesting that by modifying two ingredients in plants that we can change the iron content in rice and therein help millions of starving people in Africa. http://dixie.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwTV27CgIxEAyiYC1oWn8gRzbJXXK1eogvLDwfZV5bCqL_j3ungtWy1RQ7zLAsyzA21xWqjLoyADoE8hRvfZQul75WqPvUuebodht33lfLPzVvJmyQ71PWNqvTYi2-YQAignZGuKSy7UJVjKW9CoPUkeCJPZ3LJPAykAYn6O5UmSxXuYgmSiwTgA11RJixIS3UmbMR0mCpkthyAuZsfK0vrbttD5928muLZ__4VDxenLS954XQhXwDrkc1JQ New teats in detecting GMOs’. It is becoming increasingly more difficult to detect the use of GMO’s in our food. With this new challenge comes new ways of testing for this modification. Were do we start? What has been modified, and what baseline if any is there? http://dixie.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwNV3JCgIxDC2i4HlAe_UHOkzb6XZWB3HDg-NyTLejIPr_GDt6CrkFEt7LgyyELKTOImWpW86l98gpYCA0NilwIsvyda472f3WXg56NYwdFvDqKjJKjxnpu_V5uWG_ZwAscGsMEy42SqVskTA99z5wlYIHsEIGbMkxlBStj-Z70Eq3EIEjt4ID3aqYUHLxORmjoE6UTDImFi2CLUVkpGR6c9fe3nfHwa3-bv0qi0_1800R20tdMFk3Hz6tNkk Those against GMO’s. Obviously there are those that are against the modification of our food as well as the modification of any organisms. Messing with nature or the natural way of things is unaccepted by many and they give fact after fact how GMO’s are affecting the health of not only Americans but the entire world population. They paint GMO’s as a destructive approach to humanity. http://dixie.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwY2BQMDZLM0pNMzYzMTQ0TkoC1imJ5onJBhappomWRmnG4Fvn3AIsfLwswnzNXCBHM4FLczchBqbUPFEGOTfXEGcPXVjRGJ-SkwM6Whd0NJk5MDmKMbAAe8ap4gysacAYAtLAUlMcaII4A0eEZXioRaS3H4QrBOPqFYN3MOkVlogDC2lwBOsa6xkAAOh8J_g Identifying and labeling GMO’s. It is important to be able to identify those food sources that have been modified in one way or another. It is difficult to establish what is an original un-molested organism and that of an organism that has been modified in some cases. With the development of these labeling technics we will be able to correctly label organic organisms form those that have been treated with GMO’s. http://dixie.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwY2BQMDZLM0pNMzYzMTQ0TkoC1imJ5onJBhappomWRmnG4Fvn3AIsfLwswnzNXHgQhZObEANTap4og5yba4izhy6saIxPycmJN7IEnWQGTI-GhmIMLMCecao4A2saMIaANLDUFAeaIs7AEWEZHmoR6e0H4QrBuHrF4B1MeoUl4sBCGhzBusZ6BgDrUigB Peoples problem with stem cell research. Obviously most people have a problem with embryonic stem cells because of the question……when does life begin? Some view the destruction of embryos as murder. Another issue is that some are viewed as playing God. http://dixie.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwRV09CwIxDC2i4OB0oF39Az36dW06q4eoJw6eH2Pba0dB9P9jPBWnEAhkSPLeyxBCyFyZLFNWRguhQkBO8dZHDqnyTmbVf52rD7DbwKkxy8kfnOqCDNJtStp6dVys2fcZAIvIMpYFi6uUyG8933GtkvFSZLCdj1p3qJJjFMKg3FUVzngEGTBCOwCXg4sycDEjQ1yoEyWjjIVFi2BLMTkl44s7t3Dd7j9u8XPLR3_4VN6fFLG97wumSv4Coy00-g Uses of adult human stem cells. There is another method that is being used to harvest stem cells. This is with adult cells from bone marrow, umbilical cords, and the farming of stem cells from the nasal cavity and other locations in the adult body. http://dixie.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwRV09C8JADD1EwcFJ0K7-gZb0rk2vs1rELxzq15jrXUZR9P9jWhWn5E0ZEl7yhvCUmhlkHdhglqbGOdkpVFADNuRUajad61x1sNu1Pe1wMfqTWTVWvXCbqLpa1vNV_DUDiO-5KF7Pzopaw4KCBvRyZGi0Bj0Q-9YzmYAzCtwEQu8AwRU5Z-AaKNvMmHSq-qKnQ6QGLH2VKFwbSe1IDS_l-Wivm_0Hjn8weXZ_T8njFQm1d2MRmwTe9iw18Q Stem cell possabilities and lungs. Stem cell research is fairly new and in its infant stage (no pun intended). Scientists are using stem cells on all kinds of injuries and diseases. Among these diseases is lung disease and cancers. The idea is that these stem cells will be used to establish new tissues to replace the tissues that have been damaged. Lung tissue is one tissue in the body that once destroyed, it will not regenerate of repair itself. http://dixie.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwRV27CsJQDL2IgoNTQe_qD7T09j47q0V84WB9jLltMgqi_49pVZzCIUOGJOckQ4gQc-2oQNLOKKVjZE0BD00e0EJZkO6_zlXHsNuE894tJ3-yqhIxwPtU1NXqtFin32cAadNN0WmMBqx2bfSWPHqEUPLuwurvKaBrLWgFhgADu7llrXGE0TSkWuqqzKqZGPJCjVKMiBPLlslWcnApxtfyUofb9vCByQ9mz_7wKXu8JHN7XxepzvI3Tog2jg Potential of stem cells and quality of life. It is hard to understand the drive for stem cell research by those who have never experienced true lose. The possibility that stem cell research can improve the quality of life for millions of Americans as well as Millions more across the globe is a very real possibility. With the right backing from the Federal Government and others around the world, it is possible that stem cells could be the cure for hundreds of diseases as well as hundreds of injuries as well increasing the quality of life for millions! http://dixie.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwRV27DsIwDIwQSAxMSJCVH0jVxm2TzECFeImB8hjj1GFDQvD_wi0gJusmDz6ddYN9QsygjJoilHmWASLvFG98SC0V3ukIXepcdbDbtT3tysXoL2rVWPToPhF1tTzOV-obBqBubCkKlVtHpvHko3E-IIGJ6Nrn5iVFJmGD7PMa9hK8YSGkQLqN1kLjjEb0wUE2FX021CTFIPJgubLYSm4uxfDizrW9bvYfOP7B5NkdPiWPl2Rt73ihIEnfJL817w

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This weeks read was interesting; I had heard that Hitler at one time was an aspiring artist and that he was homeless and a vagrant at one point in his life. I did not know that the turning point, or the reason that Hitler felt that he would be a great leader came from a five hour symphony that he and his friend attended as youths. It is hard to say weather the world would have been better off if Hitler would have been accepted into art school or if there would have been another leader who would have filled the shoes of Hitler in his absence. The answer to this question we will never know. I agree with Gotschell when he explains that ink is the master of mystery, tears, fear, and triumph! That is the great thing about fiction, we can make it as exciting as we want, the hero can always win, and villain we can understand and sometimes sympathize with them as well. It is no wonder that the human race not only loves fiction and story telling, but needs fiction and story telling. Story telling has become a part of humanity. It is the way we relax and release energy, it is the portrait of our dreams, it is an escape from our mundane lives. Ink to paper is as important to the body as oxygen to blood. Without story telling, without fiction, we as a human race would cease to exist. At least in the way we have become familiar with today! So I agree very strongly with Gotschell that story telling and fiction are not optional but necessary in the human experience. My research with GMO’s is an ongoing process. There are those on both side of this debate to whether GMO’s are good for the future of the human race, and then there are those that claim that GMO’s are the reason that America is the most over weight country in the world, that the morals of the American people are off center. Also thos that support the sciences and that GMO’s are a purer form of organisms and that they are being used in other ways to improve the quality of life not only for Americans but everyone around the world.

The Moral of the Story

In reference to the reading this week “The Moral of the Story” I found it interesting the correlation between religion and biology. Let me explain; religion takes a group of people with the same beliefs and puts them into a group where they can be successful in the way they think a like. The same goes for biologists; by taking like-minded individuals greater ideas can be accomplished and brought to reality. With my second emphasis of human communication I made the connection that all story is communication, it is the way that the story is told as to the impact it will have on an individuals life. But the same can be said for story tellers alike; if like minded individuals are able to come together much like a religious sect, those individuals will give themselves a greater opportunity to be successful. My research project would be to clone each individual so that in the future if you were to encounter any physical defects, you would have a clone that you could take a kidney from, a heart, or any other organ that would be an identical match. There would be doctors and scientists that would be in charge of harvesting, or raising this clone in a healthy environment so that the maximum potential could be taken from your clone and given back to you. This project would also need teachers and others to teach the clone how to read and write, how to communicate with the other clones that were being harvested for other individuals. Of course there are ethics and morals that come into play in this scenario, but we will not get into that. This particular experiment will solve some of the problems we face with disease and sickness. With the success of this experiment you would have an identical twin in the world that you could use for spare parts essentially.