Statistics in Medicine 2003; 22; 1837–1848) developed a formula to calculate the age-conditional probability of developing a disease for the first time (ACPDvD) for a hypothetical cohort. The novelty of the formula of Fay et al (2003) is that one need not know the rates of first incidence of disease per person-years alive and disease-free, but may input the rates of first incidence per person-years alive only. Similarly the formula uses rates of death from disease and death from other causes per person-years alive. The rates per person-years alive are much easier to estimate than per person-years alive and disease-free. Fay et al (2003) used simple piecewise constant models for all three rate functions which have constant rates within each age group. In this paper, we detail a method for estimating rate functions which does not have jumps at the beginning of age groupings, and need not be constant within age groupings. We call this method the mid-age group joinpoint (MAJ) model for the rates. The drawback of the MAJ model is that numerical integration must be used to estimate the resulting ACPDvD. To increase computational speed, we offer a piecewise approximation to the MAJ model, which we call the piecewise mid-age group joinpoint (PMAJ) model. The PMAJ model for the rates input into the formula for ACPDvD described in Fay et al (2003) is the current method used in the freely available DevCan software made available by the National Cancer Institute.Fay, Pfeiffer, Cronin, Le, and Feuer ( Fay, Pfeiffer, Cronin, Le, and Feuer  showed hHere we detail two more complicated models for the rates. The first model is a segmented regression model or joinpoint model for the rates, where the rate function is a series of linear functions that join at the mid-points of the age groups, and the rate function is constant before the first mid-point and after the last "mid-point" . We will call this model the MAJ (mid-age group joinpoint) model for the rates. In Figure Notice that the MAJ model gives a more smoothly changing and probably a better modeled rate. The only place where the MAJ model may not perform better than the piecewise constant model is at peaks or valleys, where there may be some bias. In Figure A problem with the mid-age group joinpoint model is that it requires numeric integration for its calculation. The second model uses a series of piecewise constant values to approximate the mid-age group joinpoint model. We call this second model the PMAJ (piecewise mid-age group joinpoint) model. The PMAJ does not require numeric integration, so it is much faster than the MAJ model. The PMAJ model is a piecewise constant model that only differs from the piecewise constant model of Fay et al  in that The outline of this paper is as follows. The review and overview section reviews the issues in estimating the age conditional probability of developing disease from surveillance data. This section includes a motivation for using this type of statistic to describe population data. The review and overview section additionally gives graphical descriptions of the MAJ and PMAJ methods. The paper is structured so that readers not interested in the details may skip the next two sections and the appendix, which give precise and notationally involved definitions of the MAJ estimators. The examples and discussion section gives examples of the estimator of ACPDvD using three different methods for estimating the rates, the simple piecewise constant method proposed in Fay et al , the MAJConsider a surveillance program like the SEER program of the U.S. National Cancer Institute. This program attempts to count every incidence of cancer within the catchment area of the program. Because cancer is a disease in which the rates of the disease are highly dependent on age, in order to give interpretability to the counts within the SEER registries, we must somehow account for the age distribution in the popoulation.One simple and popular statistic is the age adjusted rate or directly standardized rate (DSR). In the SEER Cancer Statistics Review  DSRs areThe ACPDvD uses cross-sectional incidence and mortality rates to estimate the age-conditional probabilities of developing disease in a hypothetical cohort in which we assume the age specific rates do not change over time. This gives a personal interpretation to the cross-sectional data, allowing statements like the following: if the incidence and mortality rates remain at their present values , then a female born today would have a 13.5% chance of developing breast cancer over her lifetime  within each age group and divide by the total number of person-years estimated by the population. For counts of a single year, the person-years are estimated by the mid-year population of the catchment area . Note that the incident cases may include individuals who have previously been diagnosed with the cancer and have developed a new primary cancer.For the ACPDvD for any specific disease we would like the rate of first incidence per person-years alive and disease-free. Thus, there are two difficulties, (1) the usual age specific incidence rates include persons with multiple primary cancers, and (2) the denominators include persons who have previously been diagnosed. Merrill and Feuer  discuss In calculating the ACPDvD we use only first incident of the disease of interest as in , but we x and y, given alive and cancer-free at age x, may be written as the fraction,In the following let the disease of interest be "cancer". The ACPDvD between ages To calculate the numerator, we integrate over the probability that the first cancer occurred at exactly age a. In math notation this probability isfc(a) is a probability function representing the probability that the first cancer occurred at exactly age a. One key result described in Fay et al , the PMAJ method, and the percent difference. In general, the two methods agree to within about 2 percent.Click here for file


Investigating individual, as opposed to predetermined, quality of life domains may yield important information about quality of life. This study investigated the individual quality of life domains nominated by youth with type 1 diabetes.Eighty young people attending a diabetes summer camp completed the Schedule for the Evaluation of Individual Quality of Life-Direct Weighting interview, which allows respondents to nominate and evaluate their own quality of life domains.The most frequently nominated life domains were 'family', 'friends', 'diabetes', 'school', and 'health' respectively; ranked in terms of importance, domains were 'religion', 'family', 'diabetes', 'health', and 'the golden rule'; ranked in order of satisfaction, domains were 'camp', 'religion', 'pets', and 'family' and 'a special person' were tied for fifth. Respondent age was significantly positively associated with the importance of 'friends', and a significantly negatively associated with the importance of 'family'. Nearly all respondents nominated a quality of life domain relating to physical status, however, the specific physical status domain and the rationale for its nomination varied. Some respondents nominated 'diabetes' as a domain and emphasized diabetes 'self-care behaviors' in order to avoid negative health consequences such as hospitalization. Other respondents nominated 'health' and focused more generally on 'living well with diabetes'. In an ANOVA with physical status domain as the independent variable and age as the dependent variable, participants who nominated 'diabetes' were younger (M = 12.9 years) than those who nominated 'health' (M = 15.9 years). In a second ANOVA, with rationale for nomination the physical status domain as the independent variable, and age as the dependent variable, those who emphasized 'self care behaviors' were younger (M = 11.8 years) than those who emphasized 'living well with diabetes' (M = 14.6 years). These differences are discussed in terms of cognitive development and in relation to the decline in self-care and glycemic control often observed during adolescence.Respondents nominated many non-diabetes life domains, underscoring that QOL is multidimensional. Subtle changes in conceptualization of diabetes and health with increasing age may reflect cognitive development or disease adjustment, and speak to the need for special attention to adolescents. Understanding individual quality of life domains can help clinicians motivate their young patients with diabetes for self-care. Future research should employ a larger, more diverse sample, and use longitudinal designs. Quality of life (QOL) is now recognized as an important outcome for people with diabetes. In general, diabetes has been shown to negatively impact QOL . TighterThe measurement of QOL is evolving, and a state of the art review identified numerous different QOL measures . Most QOBy pre-selecting life domains, and/or limiting items to those that are diabetes relevant, we limit our breadth and depth of understanding of youth with diabetes. While diabetes impacts nearly all aspects of a young person's life, it may not be the central, organizing construct under which all other domains fall. If a child with diabetes was asked "What is important to you?" and "How is that important thing going for you right now?" diabetes may or may not be mentioned. For example, in a sample of adolescents with type 1 diabetes, fewer than 1/3 of participants ranked diabetes as the most important life domain, the remainder rated it much lower . And wheThese questions are not of solely theoretical interest. On an individual patient basis, such information may be clinically useful. Understanding the QOL domains that are important to an individual patient gives a provider information about how to motivate that individual for improved self-care. This is true for diabetes-related life domains and those domains that are not directly diabetes-related. For example, a provider treating a child who values athletics could use this information to motivate the child to improve diabetes self-care by demonstrating to him that improved glycemia could enhance his athletic performance. Using a patient's own value system to promote healthy behavior has been advocated by others  and is cThe Schedule for the Evaluation of Individual Quality of Life-Direct Weight (SEIQoL-DW) is a theory based  structurParticipants were campers, and young counselors who had previously been campers, at an overnight summer camp for children with diabetes. The camp serves children with diabetes in northern New England. One hundred and twenty campers from 8–15 years old attend a 2-week session. The majority of the staff has diabetes.For campers, parents completed a survey of demographic and disease variables for themselves, their family, and their child with diabetes. Counselors who participated in the study completed the survey of demographic and disease variables themselves. Demographic variables included family structure, socioeconomic status, school performance, and race/ethnicity. Disease variables included disease duration, treatment regimen, HbA1c (gold standard measure of glycemic control), frequency of complications, and emergent use of health care services.As described by Browne et al , there aIn the second stage, the respondents rate each domain on a 0–100 mm vertical visual analogue scale anchored at the two extremes by the terms 'best possible' and 'worst possible'. These anchors are designed to allow individuals to use their own criteria when assessing their status within each domain.The third stage involves a weighting procedure wherein the respondent judges the relative importance of each domain. In the original version of the SEIQoL a technique known as judgment analysis was used. Because of practical limitations of judgment analysis, a direct weighting procedure has been developed . The dirStudies have shown the SEIQoL to have good internal consistency, ranging from .6 to .9 -26. It hThis project was carried out in accordance with the American Psychological Association guidelines for ethical conduct of research. It was approved by the University of Connecticut Health Center's institutional review board. One week prior to the two-week camp session, a letter was sent to the parents of campers, describing the study. Parents were sent a consent form for themselves, an assent form for their child, and a survey of disease and demographic data. Upon their arrival at camp, the materials were collected from parents and reviewed for completeness. Sixty one percent (n = 73) of campers and parents handed in completed questionnaires on the first day of camp. The most common reason given for not participating was lack of interest on the part of the child. During the 2-week camp session children were pulled one at a time from regular camp activities and administered the SEIQOL-DW. Participants were allowed to choose a sugar free treat  for their participation.During the one-week of pre-camp , counselors with diabetes who had previously been campers were approached and invited to participate in the study. Informed consent was obtained, and staff members were administered the SEIQoL-DW individually at their convenience. All eligible staff chose to participate (n = 17).Two interviewers completed all 90 interviews. They were the first author who is a clinical psychologist, and the third author who is a medical student with an M.P.H. in health behavior. Both interviewers studied the SEIQoL-DW manual, role-played giving the SEIQoL-DW, and conferred about validity, boredom, and fatigue scoring.Consenters were compared to the total camp population for systematic differences. Results of a chi square test show no significant differences in gender. Results of an ANOVA show no significant differences in age, HbA1c, or duration of diabetes. Likewise, there were no significant differences between campers and counselors for quality of life total scores, gender, type of diabetes, age of diagnosis, number of daily injections, hypoglycemic episodes in the previous month, as well as number of sick days, hospitalizations, ketoacidosis episodes, and emergency room visits in the previous year.On average, participants were 13 years old, came from 2-adult homes (74%) with 1 or 2 siblings. All but one participant were European American. Most did "well" or "very well" in school (69%), and had parents with at least 2 years education beyond high school. Participants had diabetes for an average of about 6 years and had been attending diabetes camp for an average of 4 years. All were on multiple injection regimens or insulin pumps (n = 29), and their average glycemic control was fair (mean HbA1c = 8.02). Participants had missed an average of 3 days of school in the last year due to their diabetes, and had experienced about 6 episodes of hypoglycemia in the previous month.Data from ten children were deemed invalid due to interviewers' judgment that the participant was unable to understand the SEIQoL-DW task. For example, one child did not understand the concept of 'importance', and instead only rated domains in terms of his happiness with them. All children whose data were deemed invalid were under 12 years old, with a mean age of 9.25. The data from these ten children (1/3 of those children under 12) are deleted from the following results. Table Of the 400 total domains nominated by the 80 participants with valid data, only 21 domains (5%) were nominated with the assistance of the standard list. These 21 were for the third, fourth, and fifth domains. Thus, every respondent could nominate at least 2 domains without suggestion, and only a handful needed help with the additional 3 domains. Table The most frequently nominated domain was 'family'. Family was nominated by 76/80 respondents. Answers were coded 'family' if the participant used the terms 'family' or 'parents'. Reasons given tended to involve either instrumental support  or emotional support (they love me and I can go to them with problems). Many respondents stated that their families were important because they helped with diabetes, e.g., purchased diabetes supplies, drove them to doctor's appointments, cooked nutritious food, and helped with treatment decisions. Results of a bivariate correlation indicate a significant negative correlation between age of respondent and the importance rating given to the 'family' domain, r = -.34, *p < .01. There was no relationship between respondent age and 'family' satisfaction.The second most frequently nominated domain was 'friends'. Respondents tended to refer to a group of friends, rather than an individual friend. Friends were generally valued for their emotional support, their companionship, and the participant's ability to relax and have fun with them. The ability to "be myself" and still be accepted by friends was a common theme. Results of a bivariate correlation indicate a significant positive correlation between age of respondent and the importance rating given to the 'friends' domain, r = .35, *p < .01. There was no relationship between respondent age and 'friends' satisfaction.School was nominated by many respondents as an important life domain. School was deemed important for a variety of reasons. Some respondents stated that school was important because learning is important in its own right. Some stated that school performance was important to assure acceptance to a good college and have a good job, or because their school performance was important to their parents. Age was not related to 'school' importance or satisfaction.The nomination of 'diabetes' as an important life domain was common. However, respondents' explanations for its nomination were varied. One type of response referred to taking proper care of diabetes in order to avoid negative consequences. These responses included things like eating well, self-monitoring blood glucose, keeping active, and taking injections on time to avoid medical complications, hospitalization, or death. Respondents who gave this sort of answer were fairly concrete and said things such as "I have to take my shots or I will end up in the hospital". Thirty four responses fell into this diabetes 'self-care behaviors' category. Another type of diabetes response referred to living well with diabetes. These responses included things like doing enjoyable activities despite diabetes, successfully negotiating diabetes treatment with parents, feeling proud of self when diabetes is controlled, receiving emotional support for diabetes, and keeping self, friends and family from worrying about diabetes. Respondents who gave this sort of answer provided more abstract explanations, and said things such as "I can't let diabetes stop me" and "It's important that people around me understand what it's like for me to have diabetes". Eleven responses were of this type. Results of an ANOVA with rationale for diabetes nomination (self care vs. living well with diabetes) as the independent variable, and age as the dependent variable revealed that those who provided 'self care behaviors' as a rationale were younger (M = 11.8 years) were than those who provided living well with diabetes as a rationale (M = 14.6 years) F  = 2.88, p < .05. There were no group differences for age of diagnosis, number of daily injections, hypoglycemic episodes in the previous month, as well as number of sick days, hospitalizations, ketoacidosis episodes, and emergency room visits in the previous year. Among those who nominated 'diabetes' as a domain, age was not related to 'diabetes' satisfaction.Respondents who nominated 'diabetes' as a domain were asked whether or not they would do so if they were in a non-diabetic environment such as school, as opposed to a diabetes summer camp. All respondents stated yes, they would nominate diabetes. However, some went on to say that they might not use the word 'diabetes' per se, and instead might use the word 'health'. Twenty four respondents did in fact nominate 'health' as a domain (but not diabetes). Explanations for 'health' focused on what might be considered more general wellness. Individuals who nominated 'health' said things like "I have to be healthy in order to do the things I enjoy", "I like staying fit", "you can't be happy without good health", and "when I don't feel well I'm in a bad mood". Six other respondents nominated both 'diabetes' and 'health' as separate domains. Results of a one-way ANOVA reveal that respondents who nominated 'diabetes' only were significantly younger (M = 12.9 years) than respondents who nominated 'health' only (M = 15.9 years) F  = 4.53, p < .01. There were no group differences for age of diagnosis, number of daily injections, hypoglycemic episodes in the previous month, as well as number of sick days, hospitalizations, ketoacidosis episodes, and emergency room visits in the previous year. Among those who nominated 'health' as a domain, age was not related to 'health' satisfaction.Many domains were nominated by this sample that are not included in the standard list. They include 'diabetes', 'school', and 'camp', all of which clearly reflect that this was a sample of school aged young people attending a camp for children with diabetes. Some respondents nominated a 'special person' in their lives, such as a teacher or a coach. Other novel domains were nominated the explanations for which are less obvious. One domain involved 'mental attitude' and referred to taking the right approach to life and maintaining a positive outlook. Another involved 'the golden rule' and referred to treating others as one wants to be treated, with fairness and respect.As stated above, the most frequently nominated domains were 'family', 'friends', 'diabetes', 'school', and 'health'. Domains ranked by importance were 'religion', 'family', 'diabetes', 'health', and 'the golden rule'. Domains ranked by satisfaction were 'camp', 'religion', 'pets', 'health', and 'family' and 'a special person' tied for fifth.Total SEIQoL-DW scores ranged from 34.9 – 97.7, M = 78.1, SD = 11.2. Normative data for children are not available. However, these values are similar to those of a small clinic sample of adolescents with type 1 diabetes that reported SEIQoL satisfaction data only [The purpose of this study was to explore the individual QOL domains of youth with diabetes. Consistent with previous findings  results The young people in this sample nominated nearly all the life domains that are offered on the SEIQoL-DW standard list (with the exception of finances). They also went on to nominate additional domains, notably what we have termed 'mental attitude' and 'the golden rule'. These domains are some of the more fundamental aspects of quality of life but are not typically nominated in adult samples. Their nomination raises interesting questions. It is possible that youth are more concerned with these life domains than adults. This may be particularly true for children at overnight summer camp where community living and group cooperation is fundamental and continually reinforced. It is also possible that people with diabetes are more concerned with these life domains than their non-diabetic counterparts. Perhaps these respondents, who have experienced a major negative life event with their diabetes diagnosis and may also have suffered teasing or rejection due to this diagnosis, are more sensitive to issues of positive thinking and treating others with respect. Because this was an uncontrolled study, these are, of course, hypotheses that can only be tested with further investigation of controls.Nearly all respondents nominated a domain that reflected physical status. Younger respondents (who were on average 12 years old) were more likely to focus specifically on diabetes, and emphasize the importance of diabetes self-care behaviors. These respondents stressed adherence to the diabetes treatment regimen in order to avoid medical complications. Older respondents (who were on average 15 years old) were more likely to focus on general health and emphasize the need to live well despite the difficulties of diabetes. These age related data need to be interpreted cautiously due to small sample size, homogeneity of the respondents, and the cross sectional design of the study. The literature would benefit from further use of individual QOL measures with children and with chronic illness populations such as diabetes, in longitudinal designs. Nonetheless, these data do suggest a change in how diabetes is conceptualized during adolescence.There are several possible explanations for these age differences. First, Piaget proposed that formal cognitive operations begin in adolescence. With formal operations, adolescents gain the ability to think about their own thinking, to imagine many possibilities, and to mentally generate possible outcomes and thus rely less on real objects and events. Abstract thought becomes possible. The observed shift in focus from the concrete to the abstract – from 'diabetes' to 'health' and from 'self-care behaviors' to 'living well' – may be a reflection of the cognitive development that occurs with formal operations. Studies have demonstrated a systematic progression of children's understanding of illness that corresponds to Piaget's framework ,31. OtheSecond, as they go through adolescence, youth with diabetes may view their physical well being differently due to more extensive and broadened life experience. Older youth may realize that strict adherence to the medical regimen comes at a cost of an inflexible lifestyle, and may value quality of life over strict medical management. They may become more willing to make compromises in self-care in order to participate more fully in normal activities. They may also, for the first time, be in a position to make these compromises as parental control of day-to-day diabetes management wanes in adolescence. Third, this shift may reflect adolescents desire to fit in with peers, normalize their disease experience, and assimilate their illness. Viewing physical status in terms of health, rather than diabetes, and diabetes in terms of living well, rather than disease management behaviors, serves these functions.This shift in diabetes conceptualization could serve to be adaptive, or conversely it may herald the poor self-care and decreased glycemic control that is often noted in adolescence and young adulthood. Wysocki, Hough, Ward and Green  found thIn addition to differences in domain nomination, we also observed age effects for the importance assigned to domains. As would be expected, age was significantly positively associated with the reported importance of friends, and a significantly negatively associated with the reported importance of family. As young people grow older, the value they place on family and friends changes, and peers become increasingly important. These data are consistent with previous findings that children with diabetes find friends more helpful in diabetes management than many adults . InterveThese data should be interpreted cautiously for several reasons. First, they reflect a select sample of white, higher socioeconomic status, high academic achieving children, many of whom have had several years of diabetes camp experience. This group may nominate different life domains, and endorse a higher QOL, than children who come from more impoverished environments without disease specific psychosocial experiences. These findings should be viewed tentatively until findings are replicated with larger and more diverse samples, in longitudinal designs that employ controls.This article reports age-related differences in health related quality of life domains in youth with type 1 diabetes. It was found that younger respondents nominated 'diabetes' as a domain and focused on 'self-care behaviors', whereas older respondents nominated 'health' and focused more on 'living well with diabetes'. Although limited by sample size and homogeneity, these findings point to age related differences that may help explain deteriorating glycemic control during adolescence. What is clear is that development into maturity is a difficult task made more difficult by diabetes, and that special attention must be given to this population. The Society for Adolescent Medicine  and the JW conceived of the study, and was responsible for design, analysis, and manuscript preparation. GA assisted with data analysis, and manuscript preparation and revision. SL carried out many of the interviews, assisted with data recording, data entry, and study coordination.


To keep a cell healthy, proteins must go to the right places within a cell. To direct proteins to specific areas of the cell, they're marked with tags akin to zip codes on mail. These tags can direct one protein to the cell's nucleus, where it regulates gene expression, say, while another is sent to the hinterlands of the cell membrane, where it receives environmental signals. Protein targeting is crucial even as cells are building proteins—otherwise, for example, proteins won't fold into the proper shape.There's a pair of proteins that, across all organisms, plays a key role in protein targeting. Called Ffh and FtsY in bacteria, these proteins each have an active and inactive state; only when they're in their active state can they bind each other and deliver other proteins to their proper location. Both these proteins are GTPases, a class of proteins that work as molecular switches. However, among GTPases, Ffh and FtsY are unique. Other GTPases switch between active and inactive states by binding different forms of a small, energy-carrying molecule—either GTP or GDP. Such GTPases often require the help of other proteins to switch states. Ffh and FtsY, on the other hand, almost always have GTP bound. And when they interact, they change each other's state—allowing each other to convert GTP to GDP—without the help of other proteins. But researchers didn't know exactly how these proteins interacted or how they switched between their active and inactive forms.PLoS Biology, Shu-ou Shan and colleagues have found that when Ffh and FtsY bind and then activate each other, they likely go through an unusual, multi-step process in which the proteins change shapes, flexing so that different parts of the proteins become active at each step.Now, as reported in this issue of The researchers mutated 45 different sites in the gene that encodes the FtsY protein to produce a bevy of mutant proteins with different properties. The researchers chose mutations that produced amino acid substitutions at sites in the FtsY protein that have been preserved through evolution, and so are presumably crucial for the protein's function. These sites, it turns out, are all on the protein's surface where it interacts with Ffh.The mutant versions of FtsY varied in how well they bound to the normal version of Ffh and how quickly the two proteins activated each other. The researchers were able to sort the different mutations into four different classes based on the type of problem the proteins had: some bound Ffh very loosely, some bound Ffh well but only weakly turned on its GTPase activity, and so on. All of these mutations would presumably foul up the protein targeting system, so this explains why certain amino acids have been preserved through evolution.Both Ffh and FtsY change shapes as they bind, activate each other's GTPase activity, then cleave GTP and release each other, the researchers infer. They don't have direct evidence for these shape changes, but the postulated bends and twists during interaction are consistent with the build of the proteins. These shape changes, they speculate, could switch different parts of each protein between active and inactive states. By showing how this unique type of GTPase switch likely works, Shan and colleagues have helped explain how cells target proteins to specific areas—and perhaps have paved the way for others to find similar switches elsewhere within cells.


Over the past decade RNA interference (RNAi) has emerged as a natural mechanism for silencing gene expression. This ancient cellular antiviral response can be exploited to allow specific inhibition of the function of any chosen target gene. RNAi is proving to be an invaluable research tool, allowing much more rapid characterization of the function of known genes. More importantly, RNAi technology considerably bolsters functional genomics to aid in the identification of novel genes involved in disease processes.This review briefly describes the molecular principles underlying the biology of RNAi phenomenon and discuss the main technical issues regarding optimization of RNAi experimental design. In 1998 Fire and coll. coined the term RNA interference (RNAi) referring to the phenomenon of post-translational silencing of gene expression that occurs in response to the introduction of double-stranded RNA (dsRNA) into a cell [Introduction of long dsRNA into a mammalian cell triggers a vigorous nonspecific shutdown of transcription and translation, in part due to activation of dsRNA-dependent protein kinase-R (PKR) . ActivatRNAi is a highly conserved mechanism throughout taxonomical species . In addiBesides gene silencing, RNAi might be involved in other phenomena of gene regulation. DNA/RNA interactions are known to influence DNA methylation. It appears that RNAi can also function on this level by methylating cytosines as well as CpG sequences more classically associated with methylation. If the target sequence shares homology with a promoter, transcriptional silencing may occur via methylation. Moreover, RNA appears to interact with chromatin domains, which may ultimately direct DNA methylation. Studies of C. elegans have shown that RNAi can spread among cells through mechanisms that may not hinge upon siRNA . The sysSeveral strategies for inducing siRNA-mediated gene silencing have been developed, each of them presenting specific advantages and disadvantages Table .Synthesis, purification, and annealing of siRNAs by industrial chemical processes  is becomSuppression of gene expression by RNAi is generally a transient phenomenon . Gene exSeveral crucial considerations should be beard in mind while designing RNAi experiments. The below examples regard RNAi experiments performed with chemically synthesized siRNA.1. The first step is to design a suitable siRNA sequence. A growing number of libraries of validated siRNAs directed toward some frequently targeted genes are available. However, if the gene of interest has not been targeted using siRNA before, a novel siRNA must be developed. In mammalian cells RNAi is mediated by 21- to 23-nucleotide siRNAs containing symmetrical two nucleotide 3' overhangs. Given a siRNA sequence alone, it is not currently possible to predict the degree of gene knockdown produced by a particular siRNA. Nevertheless, several observations have been made that can be taken into account to increase the probability of producing an effective siRNA. The chief variable is the gene target site. Generally, it is recommended that a target site located at least 100–200 nucleotides from the AUG initiation codon is chosen. Targets within 50–100 nucleotides of the termination codon should instead be avoided. The 5' and 3' untranslated region (UTR) should also be avoided, since associated regulatory proteins might compromise RNAi. This is just a general recommendation, as some siRNAs targeting the 3' UTR have also been shown to induce RNAi . Numerou2. The structural characteristics of the siRNA molecules are another crucial aspect to be considered while designing RNAi experiments. SiRNA of 21 nucleotides with 3'-d(TT) or (UU) overhangs are considered the most effective . Despite3. To induce RNAi, siRNA must be transfected into the cells of interest. Several transfection reagents exist, the most commonly used being liposomal or amine-based. In some cases electroporation may be used, but cell toxicity can be high with this technique . Cell li4. Recently, experimental design features have been suggested to guarantee the rigor of RNAi experiments . Due to 5. The effect of RNAi should be quantified at both the mRNA and the protein level. The knockdown of a protein should be probably evaluated after mRNA reduction has been proved: in fact, a reduction in protein levels not accompanied by a decrease in mRNA might indicate that other mechanisms are at work, such as RNAi mediated by microRNA. Northern blot analysis is considered by many to be the gold standard. Real-time reverse transcriptase polymerase chain reaction, incorporating internal controls to quantify "housekeeping" gene transcript levels, can also be used . ProteinRNAi is now commonly used in biological and biomedical research to study the effect of blocking expression of a given gene. As the effect is rarely complete, it is generally termed a "knock-down" to distinguish it from the "knock-out" achieved by deletion of the gene. Although significant advances have been made as compared to previous methods, RNAi has its own limitations. Not every sequence works, most researchers reporting a success rate of about one in three. Moreover, although the effects are generally believed to be highly sequence-specific, some doubts remain as to whether or not some of the observed effects are "off target." Some residual activation of the interferon system has been reported, as well as degradation of closely related, but non-identical, mRNAs. Nevertheless, RNAi remains the most promising functional genomics tool recently developed. DNA microarray technology has now enabled the level of expression of every gene in the genome to be determined under any condition ,35. This


Phosphoinositides mediate one of the intracellular signal transduction pathways and produce a class of second messengers that are involved in the action of hormones and neurotransmitters on target cells. Thyroid hormones are well known regulators of lipid metabolism and modulators of signal transduction in cells. However, little is known about phosphoinositides cycle regulation by thyroid hormones. The present paper deals with phosphoinositides synthesis de novo and acylation in liver at different thyroid status of rats.Myo-[3H]inositol, [14C]CH3COONa, [14C]oleic and [3H]arachidonic acids were used to investigate the phosphatidylinositol (PtdIns), phosphatidylinositol 4-phosphate and phosphatidylinositol 4,5-bisphosphate (PtdInsP2) synthesis. 1-methyl, 2-mercaptoimidazol-induced hypothyroidism was associated with the decrease of myo-[3H]inositol and [3H]arachidonic acids incorporation into liver phosphoinositides and total phospholipids, respectively. The thyroxine (L-T4) injection to hypothyroid animals increased the hormones contents in blood serum and PtdInsP2 synthesis de novo as well as [3H]arachidonic acids incorporation into the PtdIns and PtdInsP2. Under the hormone action, the [14C]oleic acid incorporation into PtdIns reduced in the liver of hypothyroid animals. A single injection of L-T4 to the euthyroid [14C]CH3COONa-pre-treated animals or addition of the hormone to a culture medium of hepatocytes was accompanied by the rapid prominent increase in the levels of the newly synthesized PtdIns and PtdInsP2 and in the mass of phosphatidic acid in the liver or the cells.The experiments were performed in either the rat liver or hepatocytes of 90- and 720-day-old rats. 4 injection to the animals was followed by the time-dependent increase of polyphosphoinositide synthesis in the liver. The both long-term and short-term hormone effects on the newly synthesized PtdInsP2 have been determined.The data obtained have demonstrated that thyroid hormones are of vital importance in the regulation of arachidonate-containing phosphoinositides metabolism in the liver. The drug-induced malfunction of thyroid gland noticeably changed the phosphoinositides synthesis de novo. The L-T The phosphoinositides is a family of lipids which members play an essential role in the receptor-mediated intracellular signaling cascades, vesicle trafficking and cytoskeletal rearrangements  and, 2) in the plasma phosphoinositides and inositol 1,4,5-trisphosphate were found to be significantly lower in the hypothyroid rat hearts [3H]inositol phosphate in the hypothalamic slices, whereas the thyroxine (L-T4) completely restored the hypothalamic [3H]inositol phosphate formation [3H]inositol pre-labeled tissue oleic and [14C]linoleic acid pre-labeled hepatocytes of adult 90-day-old rats  and thur of PLD ,27. The tivation . The PLDiposomes  and stimiposomes . The reshe liver  and othehe liver . The PKChe liver ] and phohe liver  stimulathe liver  correlatats Fig. . Howevermyo-[3H]inositol incorporation into the PtdIns, PtdInsP and PtdInsP2 in the liver of the drug- and L-T4 -treated animals. The MMI administration to the rats was found to be accompanied by the decreased myo-[3H]inositol incorporation into the PtdIns, PtdInsP and PtdInsP2 in the liver  stimulate the phosphatidic acid and PtdInsP2 accumulation and did not change the PtdIns content in the liver cells, it could be assumed that in such case the L-T4 increases PtdInsP2 synthesis via phosphoinositide 5-kinase activation rather than the lipid synthesis de novo.Thyroid hormones stimulate lipogenesis in the liver by inducing the enzymes in the lipogenic pathway. The acyl-CoA-glycerol-3-phosphate acyltransferase, which is known to catalyze a rate-limiting step for the synthesis of phosphatidic acid in the rat liver, is dependent on the thyroid gland function . The L-Tatocytes . The resatocytes . It can 5-kinase  and thus3 administration to the euthyroid rats increases the saturated fatty acids and arachidonate/linoleate ratio of PtdIns in the liver cell mitochondria [It is well documented that the efficiency of polyphoshoinositide derived second messanger DAG in signaling pathways is closely dependent on the degree of its unsaturation. The unsaturated fatty acids are incorporated into the sn-2 position of the phospholipids by the deacylation-reacylation reactions. Some investigations demonstrated the changes of the fatty acid composition of membraneous lipids at the hypo- and hyperthyroid state of the rats [for review see ]. There chondria .3H]arachidonic acid incorporation into the liver total phospholipids  and decreased the content of the oleate-labeled PtdIns in the liver slices (Table 3D). The incorporation of the [14C]oleic acid into the PtdInsP2 did not differ between the liver slices of control, drug- and hormone-treated animals. As can be seen from the Table 4 and T3 levels in the blood serum, but did not remove completely the hormones from organism. The T3 content in the serum of the drug-treated animals was relatively high as compared with control animals. However, the MMI reduced the T4 level by 77%. The T4 administration to the MMI-treated rats increased significantly T3 and T4 contents in the serum. It seems possible that the 14C/3H fatty acids incorporation into the phosphoinositides was rather regulated by the T3 than T4, although the both hormones are participated in the regulation of the other phospholipids acylation in the rat liver.The MMI did not change markedly the s Figure . The L-T2 synthesis, which are the predominant substrates of PLC in the numerous signaling pathways. The both long-term and short-term effects of hormone on lipid synthesis have been determined  involved in the signal transduction in the stimulated cells, the abnormalities of the phosphoinositides synthesis at different pathological states of thyroid gland could disturb other hormones signaling in the target cells.The present data have demonstrated that the phosphoinositides synthesis de novo and arachidonic acid incorporation into phospholipids are strongly dependent on the thyroid status of organism. The marked enrichment of animal cell phosphoinositides in arachidonate and the results obtained suggest an important role of the thyroid hormones in the regulation of polyunsaturated PtdIns and PtdInsPd Figure . The L-Tynthesis ,37. Consmyo-[3H]-inositol (58 mCi/mmol), [14C]oleic acid (58 mCi/mmol) and [3H]arachidonic acid (60 Ci/mmol) – Amersham Corp. and [14C]CH3COONa (25 mCi/mmol) – BPO Isotop (Russia); silica gel from Woelm (Germany). Phosphatidylinositol, phosphatidylinositol 4-phosphate and phosphatidylinositol 4,5-bisphosphate lipid standards were obtained from Sigma (USA). T4 and 1-methyl, 2-mercaptoimidazol were from Zdorov'e Trudyaschikhsya . T4 and T3 radioimmunoassay kits were from Minsk (Belarussia). Other chemicals used were of chemically pure grade.4 (200 μg/100 g weight) 48 h prior to killing. Besides, T4 (200 μg/100 g weight) was injected to the normal rats 15 and 60 min prior to killing. Control rats received 0.9% NaCl of the same volume. The animals were starved overnight prior to experiment. The thyroid state of rats was monitored by radioimmunological determination of the T4 and T3 in blood serum.90- and 720-day-old male Wistar rats, which had a free access to food and water and were kept at 24°C on a cycle of 12 h light/12 h darkness were used for experiments. The MMI was injected intraperitoneally (1 mg/100 g weight) in 0.9% NaCl to the experimental animals every day during 16 days-experiment. In some cases, the MMI-treated rats were injected intraperitoneally by T14C]CH3COONa was intraperitoneally injected to rats four times every 30 minutes for 2 hours. The liver was perfused with 0.9% NaCl, then removed and washed in Krebs-Henseleit buffer, pH 7.4, containing 2 mM CaCl2 and 0.2% BSA. The pre-labeled liver was used to obtain 10% homogenates and to analyze the14C-phosphoinositides. Besides, the slices of unlabeled liver were labeled by incubation in the Eagle medium containing 10% fetal calf serum, 100 units/l streptomycin, 100 units/l penicillin, 13 mg/ml gentamycin and 0.1 μCi/ml of mio- [3H]inositol or 2.5 μCi/ml of [14C]oleic acid or 2.5 μCi/ml [3H]arachidonic acid for 1–2 h in 95% O2/5% CO2 atmosphere at 37°C. The lipids were extracted and analyzed as described below.The 1 mCi of lipids were scraped and transferred to the scintillation vials. Radioactivity was measured by a scintillation counter.The phospholipids were extracted according to Folch et al. , the phoribed in . The gelNAB conceived of the study and participated in its design, coordination, and manuscript preparation. OAK participated in data collection and performed the statistical analysis.


With the genome assembly archive, it is possible to examine the raw data that underlies the DNA sequence in any sequenced genome Scientists have dedicated considerable effort to decoding the genomes of an ever-growing list of species, ranging from small viruses, whose genomes may be just a few thousand nucleotides in length, to large mammalian genomes, three billion nucleotides and larger. Many aspects of life science research have benefited by the accumulation of these data, but decoded genomes could be even more valuable if important information about the genome sequence, currently being lost, were preserved. Occasionally, questions arise about a specific position in the sequence—or a variant in the sequence is observed in a new sample. At times like these, it would be helpful to be able to go back to the experimental evidence that underlies the genome sequence at that position, to see if there is any ambiguity or uncertainty about the sequence. As things stand, that's almost impossible. To understand why this is the case, it is necessary to know a bit more about how a genome sequence is put together.Haemophilus influenzae in 1995 , which are then sequenced. The sequences are assembled to generate a consensus sequence that, if all steps work perfectly, matches the original DNA molecule. Since the sequencing of  in 1995 , most baWithout really being aware of it, the bioinformaticians who assemble genomes have for years been discarding the valuable information on how all of the individual sequence fragments align to the assembled chromosomes. This loss has gone largely unremarked because the scientific community has focused its attention primarily on the end product: the final genome sequence itself. It is only natural to regard the genome sequence, which is the basis for gene discovery and for functional understanding of the biology of the organism, as the primary result of a WGS project. In reality, though, a WGS project is an experiment in which large numbers of sequencing reactions are run, followed by a combination of computational work and additional sequencing to complete the genome. Three years ago, the Trace Archive  was developed to store the raw sequence data and to facilitate dissemination of this data, but currently there is no database that captures the alignment of these reads to the published genome sequence.Many scientists would be surprised to hear that genome assemblies are unavailable. One might infer that the assembly of a genome could be reconstructed from the genome sequence and the associated traces. However, aligning the traces to the genome will generally not reproduce the assembly, both because many of the traces will have alternate possible alignments and because, in some cases, parts of the assembly are manually refined based on additional experimental data. Furthermore, only a small number of large-scale centers have the computing hardware, software, and bioinformatics expertise to allow them to assemble a large genome.http://www.ncbi.nlm.nih.gov/projects/assembly). The archive has been developed to store both an archival record of how a particular assembly was constructed and the alignments of any set of traces to a reference genome. Assemblies contained in this archive will be available in the GenBank (http://www.ncbi.nlm.nih.gov/Genbank/index.html), DDBJ (http://www.ddbj.nig.ac.jp/), and EMBL (http://www.ebi.ac.uk/embl) databases, and all underlying traces are required to be deposited in the Trace Archive.To bridge this gap, we have developed the Assembly Archive (Bacillus anthracis (the causative agent of anthrax), which have been sequenced as part of an effort to understand the detailed variation of that species. This includes the completed reference genome of the Ames strain, sequenced from a sample kept frozen since 1981, when it was originally isolated in West Texas . For the first time, the evidence behind each polymorphism in these assembled genomes will be directly accessible to the scientific community.The Assembly Archive's first entries are a set of seven closely related strains of B. anthracis bacterium (the bacterium sent through the United States mail in late 2001) in order to determine if there were any differences between it and a reference laboratory sample  are common causes of base-calling errors, because the peaks in the underlying trace data sometimes merge together. The sequence shown includes several monomer runs; several of the underlying traces are shown as well. For example, the run of six As at the far left of the figure is supported by several reads in which all six peaks are distinct, as well as other reads in which the six nucleotides appear as one broad peak. By examining data such as these, one can easily verify (or disprove) putative SNPs in this genome.Human polymorphism studies e.g.,  are a trIn contrast with prokaryotic genomes, the human genome  is diploid, and as a result many SNPs can be discovered within a single assembly, which contains the chromosomes representing the two parent organisms. SNPs can also be found through population studies in which the same locus is sampled from multiple individuals. In either case, the evidence for a SNP begins with the alignment of two different genomes. Despite the clear need for it, the original evidence for the genome itself—the assembly—is not available, and is not linked to the evidence in the Trace Archive. If it were available, many of the polymorphisms already reported could be validated, and many more SNPs might be discovered. Assemblies will also allow centers to better coordinate their gap-closing and finishing efforts, as has been recently noted .We hope that the availability of the Assembly Archive will encourage human genome sequencers, and sequencers of other genomes, to begin depositing their assemblies into this public resource, where it can be shared by all.


O(n6)time and O(n4) space algorithm by Rivas and Eddy is currently the best available program.The general problem of RNA secondary structure prediction under the widely used thermodynamic model is known to be NP-complete when the structures considered include arbitrary pseudoknots. For restricted classes of pseudoknots, several polynomial time algorithms have been designed, where the O(n4) time and O(n2) space to predict the energetically optimal structure of an RNA sequence, possible containing such pseudoknots. Evaluation against a large collection of known pseudoknotted structures shows the adequacy of the canonization approach and our algorithm.We introduce the class of canonical simple recursive pseudoknots and present an algorithm that requires RNA pseudoknots of medium size can now be predicted reliably as well as efficiently by the new algorithm. Pseudoknots have been shown to be functionally relevant in many RNA mediated processes. Examples are the self-splicing group I introns , ribosomn into unknotted structures requires O(n3) time and O(n2) space, finding the best structure including arbitrary pseudoknots has been proved to be NP-complete O(n4) timO(n6) time and O(n4) space ]]]..........}}.This grammar is useful to judge how different an experimentally determined structure is from class csr-PK. It is not useful for programming, since it is ambiguous and does not distinguish the fine grained level of detail required in the energy model.A careful discussion is required to show that each simple recursive pseudoknot, if not canonical by itself, has (a) a canonical representative of (b) similar free energy.i' and j'. It is not canonical if one of the two helices contains bulges. However, there must be at least one pair of shorter helices without bulges at i, j with i' ≤ i and j ≤ j', which serves as a canonical representative, albeit with somewhat higher free energy.Rule 1 (b) affects the length of helices that are considered in forming the pseudoknot. Let there be a pseudoknot between i, k, l, j there is a canonical one with maximal helices, whose free energy is at least as low – except for the following case: The maximal helices compete with the internal structure of u, v and w. It may be possible to contrive a structure where shortening (say) helix a – a' by one base pair allows to create two pairs with new partner bases in u and v, resulting in a structure which has slightly lower energy. Still, the free energy of the canonical pseudoknot must be very similar.Rule 2 is justified by the fact that the energy model strongly favours helix extension. Clearly, for each family of pseudoknots delineated by a' or the b – b' helix.Finally, Rule 3 requires a decision where to draw the border between two helices facing each other and competing for the same bases. An arbitrary decision here can only slightly affect free energy, as the same base pairs are stacked either on the a – E(s) denote the free energy computed for structure s. Summing up, we have shown that for each simple recursive pseudoknot K, there is a canonical one C in the search space. While we cannot prove that E(C) ≤ E(K), we have argued that this is likely, and if not, the energies will at least be close. Still, there might be another, energetically optimal canonical structure S (knotted or not) such that E(K) <E(S) <E(C). In this case, if only the "best" structure S is reported, neither K nor its canonical representative C is observed. Let Finally, let us add that the implementation described below is actually slightly more general that the "pure" csr-PK model described above: We do allow a single nucleotide bulge in either helix of a pseudoknot, which complicates the program, but does not affect asymptotic efficiency.To evaluate how well the class csr-PK covers known pseudoknots, we considered 212 pseudoknot structures from PseudoBase. The observations are shown in Table We find 172 simple recursive pseudoknots, and 40 of more general shapes. We find that 135 out of the 172 pseudoknots lie in csr-PK, i.e. they are their own canonical representatives. 11 more fall into the relaxed csr-PK, where we allow a single nucleotide bulge in Canonization Rule 1. Thus, we cover 146 out of 212 (68%). 26 simple recursive pseudoknot do not fall in class csr-PK, since they contain isolated basepairs, non canonical basepairs or one of the helices has not maximal extent.a – b – c – d – c' – a' – d' – b', where helix d – d' is very short – only two base pairs. Deleting it, helix c – c' is no longer interacting with other helices, and the pseudoknot falls within class csr-PK.Considering the remaining 20% complex pseudoknots, note that often pseudoknots in more general classes also have a good representative in csr-PK. For example, the pseudoknot of Hepatitis delta virus Figure  consistsk best structures. Secondly, we shall provide three variants of our program:There are many reasons why "the" MFE structure may only be part of what we want to know about a molecule's foldings. To deal with the problem when the optimal (knotted) structure is non-canonical, and its canonical representative is dominated by an unrelated structure, we provide two means: First of all, our algorithm is non-ambiguous, the prerequisite for a non-redundant enumeration of near-optimal structures . We can pknotsRG-mfe computes the mfe structure (or the k best), pseudoknotted or not.pknotsRG-enf picks out from the folding space the energetically best structure that contains at least one pseudoknot.pknotsRG-loc computes the energetically best pseudoknot that can be formed locally, i. e. somewhere in the sequence. "Best" is defined here as minimal free energy per base, to avoid a built-in bias towards large pseudoknots.The best local pseudoknot motif is included by adding two cases:bestPK = skipleft <<< base ~~~ bestPK ||| bestPKlbestPKl = skipright<<< bestPKl ~~~ base ||| knotO(n2) and preserve the non-ambiguity of the algorithm. If desired, an enumeration of near-optimal "local" pseudoknots is also feasible.These clauses have time complexity RNAfold and in an older version with pknotsRE), and the results in this section may improve if this model is further improved in the future.We first consider the predictive accuracy achieved by our approach. We have already evaluated the class csr-PK against the known pseudoknots, and we know that our algorithm correctly implements this class in its search space. What is really tested in the following is the adequacy of the current thermodynamic model . Let BP be the number of basepairs in the reference structure from the database or literature. We define the sensitivity as (TP/BP), selectivity as (TP/TP+FP).We compare our results to the output of RNAfold. Both, the sensitivity and the selectivity increase. Compared to pknotsRE our results are slightly better, probably because we are using the newer and subtler energy model. For example, for the sequence of hepatitis delta virus, our algorithm predicts all helices except for the very short helix 5 . For all programs the overall prediction accuracy for tRNAs is not very high. tRNAs are a known hard case for structure prediction because they contain many modified bases.We also folded 14 randomly selected human tRNAs  take about 2 hours (see Table O(cn3) with a rather large constant c. This enables us to fold sequence of length 1000 in approximately 12 hours. We can further observe that the space requirements scale quadratically with the input size, as expected.Clearly, we are able to fold sequences that are longer than equences 00 bp takpknotsRE is not strictly wasted: It is spent on assuring that the optimal folding of the input RNA sequence does not contain pseudoknots with chained interacting helices of lower free energy than the reported structure. pknotsRG does not consider such structures and hence cannot make this assertion.For a fair comparison, the reader should keep in mind that the extra time spent by In the following, we discuss extensions of the implemented model and their expected computational costCanonization Rule 1 can be relaxed further to allow larger bulges inside the helices forming a pseudoknot. As long as their number (and hence the length difference of the two arms of a helix) is bounded by a constant, asymptotic efficiency is not affected.Two examples of non-simple pseudoknots are shown in Figure kiss = kss <<< a~~~u~~~b~~~v~~~a'~~~w~~~c~~~x~~~b'~~~y~~~c'triple = trp <<< a~~~u~~~b~~~v~~~c~~~w~~~a'~~~x~~~b'~~~y~~~c'O(n6), bringing runtime back to the efficiency class of the Rivas/Eddy algorithm. But note that the space requirements remain O(n2). This is due to the fact that we now consider three interacting helices, but not arbitrary chains.Canonization can be applied as above, with Rule 3 becoming more sophisticated for the triple interaction case. This would yield an algorithm of runtime in vivo as in vitro must be understood as a hierarchical process, where small structures in close vicinity form first, and then combine to larger ones  denotes lists, and <- denotes enumerating a list of alternative values.The implementation strictly follows the outline given in the methods section, except that a considerable amount of detail related to the energy model has to be taken care of. While ADP bans the use of subscripts, our canonization ideas require to explicitly manipulate subscripts. We show the concrete pseudoknot code, but explain only the essential points. A subscript pair  = [pk energy a u b v a' w b' | k <-[i+2 .. j-1], l<-[k+1 .. j-2],k and l from the interval , and put together the results from a, u, b, v, a', w, b' under the scoring function pk. Each helix must have a minimum length of two bases. Due to stereochemical reasons one base in the front part and two bases in the back part are left explicitly unpaired; these bases should bridge the stacks. This consideration is taken over from pknotsRE. The next definitions implement canonization rules 1, 2 and 3. They determine the helix lengths, finally computed into the variables m and m'. If either of them is smaller than 2, a pseudoknot is not possible at this particular location.These line chooses cut shortens the helix b – b' as much as necessary in case of overlapping helices. The next lines define the pseudoknot components a through b', plus the local energy contribution. To avoid an extra factor of n in time complexity, the energies of maximal length helices are also precomputed in table stackenergy. If the helix b – b' must be chosen shorter than maximal to avoid overlap, a correction term has to be subtracted. This explains the negative term in the energy computation.The function front. For a full implementation of the algorithm see Left to be defined are the interior structures front, middle, and back. For reasons of space, we only show the definition of b-helix, and if the remaining region is not empty, an arbitrary list of substructures (comps) is recognized. idd, frd and pul are the corresponding functions from the energy model.This case takes care of a potentially dangling base from the v is smaller or equal to 1, the pseudoknot helices stack coaxially on each other and we further add the appropriate stacking energy. In [Overall, the energy of a pseudoknot consists of stabilizing and destabilizing terms. Where possible, we use the values from the current thermodynamic energy model . As stabergy. In  a pseudoergy. In . Finallyergy. In . Of courk, l inside , computes m and m' using the precomputed maximal helix information, and passes these boundaries to the pseudoknot compartments. Methodically, this is a use of inherited attributes with the underlying tree grammar, and appears to be a novel technique in dynamic programming, at least in its grammar oriented tradition [The first clause (knot) chooses radition ,28-30.pknotsRG can be judged from the sizes of the tree grammars required, which are summarized in Table The relative effort of implementing the three variants of pknotsRG-mfe, pknotsRG-enf, and pknotsRG-loc are available as executables and source code on the Bielefeld Bioinformatics Server [The three variants of the algorithm s Server .RG had the initial idea for the algorithm. JR developed and evaluated the software. All authors read and approved the final manuscript.Source code of pknotsRG-mfeClick here for file


Researchers from the Royal Netherlands Army are studying the potential of isolated lumbar extensor training in low back pain in their working population. Currently, a randomized controlled trial is carried out in five military health centers in The Netherlands and Germany, in which a 10-week program of not more than 2 training sessions (10–15 minutes) per week is studied in soldiers with nonspecific low back pain for more than 4 weeks. The purpose of the study is to investigate the efficacy of this 'minimal intervention program', compared to usual care. Moreover, attempts are made to identify subgroups of different responders to the intervention.Besides a baseline measurement, follow-up data are gathered at two short-term intervals (5 and 10 weeks after randomization) and two long-term intervals (6 months and one year after the end of the intervention), respectively. At every test moment, participants fill out a compound questionnaire on a stand-alone PC, and they undergo an isometric back strength measurement on a lower back machine.Primary outcome measures in this study are: self-assessed degree of complaints and degree of handicap in daily activities due to back pain. In addition, our secondary measurements focus on: fear of movement/(re-) injury, mental and social health perception, individual back extension strength, and satisfaction of the patient with the treatment perceived. Finally, we assess a number of potential prognostic factors: demographic and job characteristics, overall health, the degree of physical activity, and the attitudes and beliefs of the physiotherapist towards chronic low back pain.Although a substantial number of trials have been conducted that included lumbar extension training in low back pain patients, hardly any study has emphasized a minimal intervention approach comparable to ours. For reasons of time efficiency and patient preferences, this minimal sports medicine approach of low back pain management is interesting for the population under study, and possibly for comparable working populations with physical demanding job activities. For the last ten years, clinical researchers from the Royal Netherlands Army (RNLA) have studied the potential of physical training modalities in preventing and alleviating nonspecific low back pain (LBP) in their working population.Many military and civilian job functions in the RNLA involve heavy manual material handling and, therefore, spine-loading activities. In general, the incidence of back problems is higher in physically demanding tasks than in sedentary activities . ConcordCurrently, there is strong evidence that exercise therapy is more effective than usual care . ExercisThe specific character of military tasks nowadays, e.g. (preparation for) crisis management operations abroad, interferes with the schedules of rehabilitation programs for back-injured soldiers which, in general, take several days per week over a considerate number of consecutive weeks. Therefore, the search for effective and (time-) efficient exercise therapy protocols has led us to a specific form of lumbar extension training. Each training session consists of no more than 5 to 10 minutes training of the isolated lumbar extensors on a special training device.For a number of years, we have experience with high-intensive, isolated training of the lumbar extensors in military personnel with nonspecific LBP, by using a special training device. In this a sports medicine approach is followed, partly according to established exercise protocols ,4, in whIn individual cases, we observed satisfying to sometimes excellent results in terms of pain relief and functional restoration, when giving a training stimulus of no more than 5 to 10 minutes (1 to 2 training sessions) per week. These findings, however, need to be confirmed in a randomized controlled trial.Four main reasons led to the choice of doing research on the efficacy of this sports medicine approach for our working population with LBP.First, recent systematic reviews indicate that exercise therapy is a successful approach for the restoration of chronic and recurrent LBP, at least in the short term ,3. HowevMoreover, controversy remains regarding the impact of a training stimulus, in terms of intensity, duration and frequency, on the reduction of LBP. Different explanations for this lack of specificity are given in the literature, such as non-specific, more centrally induced training effects, e.g. a shift in pain perception , or largFrom this perspective, back strength and endurance training in CLBP patients with the use of training devices is an interesting concept for our military population. RNLA personnel are, from their very first initial military education, used to participate in physical exercise programs, including progressive resistance training on exercise machines. The RNLA is well equipped with an extensive line of modern fitness devices on all major military locations throughout the country, including state-of-the-art lower back machines. Moreover, protocolized treatment sessions with our training device take no longer than 5 to 10 minutes once or twice a week from both patient and provider, compared to (on an average) 30 minutes in regular treatment sessions. We expect this time efficiency to be highly appreciated by our personnel, who work in a typical military culture of "running into extremes": relatively quiet (maintenance) periods on the military base are interspersed with extremely busy periods shortly before and during out-of-area operations. For several target groups, longstanding and time-consuming rehabilitation programs are out of the question. For instance, recruits who drop out of their initial training because of (back) injuries, need to return as quick as possible to prevent a stagnation in their military career. For soldiers standing by for military operations, everything revolves around the mission when being commanded to be prepared within the next weeks.A second reason for our approach is that the majority of studies on LBP management consist of multimodal interventions, which include physical, behavioral, educational and/or ergonomic elements. To obtain a better view on the (relative) efficacy of either of these concepts, unimodal intervention programs like ours need to be evaluated ,8. BesidThird, the choice for a particular intervention approach depends in many cases on the stage and severity of the back problem, the extent to which psychosocial aspects are involved, and the needs and preferences of the patient. For instance, behavioral therapy is mainly focused on issues that are prevalent in chronic patients, such as low feelings of self-control or fear of movement/(re-)injury. Since the population of the present study, military employees of the RNLA, is a working population with mostly short-term, intermittent and moderately severe LBP, we chose to apply a more physical approach. As we have seen in our previous research (see the next paragraph), this links well with the health perceptions of our target population, in which perceived health problems were not severe and much more focused on physical than on mental aspects.Fourth, the efficacy of isolated extension training in chronic back patients has been studied by several other research groups as well . Althougst trial) or 8 weeks .Especially in recent years, we have scientifically studied the potential of our sports medicine approach. In two previous trials we compared the efficacy of a high-intensive, progressive resistance training program of the isolated lumbar extensors, with a low-intensive, non-progressive program of the same extend, in a group of workers with nonspecific LBP. Total intervention time of both 'minimal intervention programs' was limited to 14 sessions of 5 to 10 minutes, over a period of 12 weeks  directly after the 'minimal intervention' treatment, as well as a higher compliance to the treatment and a higher willingness to participate in physical exercise on the longer term. In the present multicenter study, we aim at identifying relevant subgroups of patients that show higher success rate due to this training approach.In a randomized, single-blinded multicenter trial, we evaluate the efficacy of progressive, isolated resistance training of the lumbar extensor muscles, compared to the usual care. The trial started in April 2002; data will be collected till the end of 2005. The source population  consists of military employees of the RNLA. Our in- and exclusion criteria are listed in table Recruitment of participants takes place during regular office hours of the military general practitioner. A brief outline of the study design is presented in Figure Almost every military location in the Netherlands has a health center, in which general practitioners, dentists and physiotherapists give primary care to military personnel of the RNLA. For the present study we selected five military health centers on the basis of: (1) representing a major part of the total military population; (2) holding at least two full-time physiotherapists, and (3) the willingness to unconditionally participate in the project.The selected military health centers include the following locations:• Amersfoort, in the middle-east of the Netherlands: approximately 15% younger soldiers on stand-by for military operations abroad (18–25 years), 25% military instructors (35+ years), 10% staff personnel (40+ years), and 46% civilian workers from supporting units (40+ years);• Den Haag, in the west of the Netherlands: approximately 90% older staff personnel (40+ years) at office work;• Oirschot, in the south of the Netherlands: approximately 75% younger soldiers in their initial military education or on stand-by for military operations abroad (18–25 years), 25% military instructors and staff personnel (35+ years);• Schaarsbergen, in the south-east of the Netherlands: approximately 65% younger soldiers in their initial military education or on stand-by for military operations abroad (18–25 years), and 30% staff personnel (35+ years);• Seedorf, in the north-west of Germany (part of the 1 German/Netherlands Corps): approximately 65% younger soldiers on stand-by for military operations abroad (18–25 years), 20% staff personnel (35+ years), and 10% civilian workers from supporting units (40+ years).All general practitioners at each of the selected study centers identify potential subjects from among their clinic's patients, according to the aforementioned criteria. Each subject is submitted to regular history taking and physical examination by the physician; checklists with standard elements for LBP have been provided to all physicians. If eligible, patients are informed about the study. All relevant information from the intake is written down in a referral; a visit to one of the physiotherapists of the center is planned within the next days.At the first visit to the physiotherapist, patients receive further information about the trial. A pre-assessment of the isometric back strength is taken. A written explanation of one of the questionnaires, in which patients have to choose the three most disabled daily activities due to back pain, is given them to take home, which allows them to make a well-considered choice at the next visit. Written informed consent is obtained from all patients who are willing and eligible to participate. At the second visit, participants undergo a baseline measurement consisting of a compound questionnaire and an isometric back strength test. At the third visit, patients are randomized into either the back strengthening group or usual care group. Directly after randomization, the first treatment session starts. Patients are allowed to withdraw from the study at any time, although the importance of full compliance of every participant is emphasized.Randomization is done by means of a computer-generated table of random numbers per study center, using a block size of ten. Prestratification is applied for the duration of the back complaints, with a cut-off point of 12 weeks, suspecting duration of complaints to influence the individual response to the exercise program. One intervention group receives a back-strengthening program; the other group receives a usual care program.The randomization is concealed, which means that the treating physiotherapist obtains the allocated treatment by means of a computer software program, by entering the name and military registration number of the patient.The study protocol was approved by the Medical Ethics Committee of the Netherlands Central Military Hospital.Subjects allocated to the back-strengthening program (BS) undergo a 10-week, progressive resistance-training program of the isolated lumbar extensor muscle groups. The program includes 14 training sessions (2 days per week) and 3 isometric back strength tests . The initial training load is set at approximately 35% of the maximal isometric back extension strength of the participant, measured at baseline. The goal of every training session is to perform 15 to 20 repetitions (reps) on the lower back machine, equivalent to approximately 50% and 70% of the one-repetition maximum (1 RM) respectively. If the subject is able to perform a higher number of reps, 2 1/2 kg weight is added in the next training session. Vice versa, if the participant is unable to perform the minimal number of reps, the subsequent training load is lowered with 2 1/2 kg. This training protocol is partly based on existing protocols , and parTraining sessions are carried out on a Total Trunk Rehab . This lower back machine is equipped with a knee-lock system and a thigh-restraining belt to immobilize both hips and thighs, allowing the participant only to move the isolated lower back.All training sessions are conducted as much as possible by the same physiotherapist. The physiotherapist pays special attention to the execution of the training in terms of pace and movement. The flexion and extension of the lower back has to be executed in the full range of motion of the participant, and movements have to be slow and controlled . During this movement, emphasis is put on the hollowing and flattening of the lumbar lordosis. Every training session is preceded by a 5-minute all-body warming-up on an arm/leg ergometer . The weight load used and the number of reps completed during each training session are recorded.Subjects allocated to the usual care program (UC) receive regular physical therapy for their lower back for at most 10 weeks, or earlier when the patient indicates to be free of complaints. Based on the physiotherapist's judgment, this could include 'hands-on' treatment  and/or 'hands-off' treatment . In the RNLA, active therapy forms are favored. To increase the contrast between both intervention programs, physiotherapists are not allowed to use the lower back machine in their usual care. Patients are not allowed to undergo co-treatment beside the interventions programs during the treatment period, nor exercise on equipment that mimics the specific components of the lower back machine.Therapeutic activities in every therapy session as well as the number of sessions are written down on a form.In this study we have chosen primary outcome measures that are most relevant to the patient and clinician: self-assessed degree of complaints and degree of handicap in daily activities due to LBP. In addition, our secondary measurements focus on several other LBP-related areas, like kinesiophobia or mental health perception.We have included some potential prognostic factors into our measurements, i.e. characteristics of the patient that possibly influence the effect of the intervention: job characteristics, overall health, physical activity, patient satisfaction with the allocated treatment, and attitudes and beliefs of the physiotherapist. This trial is mainly focused on the efficacy of our minimal intervention strategy, and not on unraveling the physiological or psychological working mechanisms of isolated lumbar extension training on LBP. Nevertheless, by including potential prognostic variables, starting points for further research into the 'black box' of this type of intervention could be identified.The following demographic variables are registered during the intake: age, time since first episode of LBP, pain radiation, treatment history, and work absenteeism due to LBP in the last year.Moreover, the status of the patient before treatment, in terms of job aspects, overall health and the degree of physical activity, is assessed using a compound questionnaire. Several job characteristics, i.e. content, relation with superior and colleagues, conflicts, and physical aspects of the job, are measured using subscales of a validated Dutch version of the Job Content Questionnaire . PhysicaOverall health is assessed with one item from the MOS 36-item Short Form Health Survey : "What dThe degree of physical activity is measured with the Short Questionnaire to Assess Health Enhancing Physical Activity , a validTo assess the attitudes and beliefs of the participating physiotherapists about the relationship between low back pain and function before the start of the study, we use the Pain Attitudes and Beliefs Scale for Physiotherapists . These aGlobal perceived effect  is measuPatient-specific functional status  is measuLow-back specific functional status is measured by the validated Dutch version of the Roland Disability Questionnaire ,24, a wiFear of movement or re-injury is measured by the Tampa Scale for Kinesiophobia , a 17-itMental health is measured by the Dutch translation of the 12-item General Health Questionnaire ,30, asseSocial health is measured by a subscale of the Impact on Participation and Autonomy Questionnaire , focusinOverall work status is measured by a 4-level item .Individual back extension strength progression was evaluated using repeated isometric measurements on the lower back training and testing machine. A detailed description of these measurements can be find elsewhere .Patient satisfaction is measured at the end of the treatment program by two 3-level items and one 5-level item, in which the degree of satisfaction with the allocated treatment is assessed: (a) "Were you satisfied with the allocated treatment at the start of the program?" (b) "Has your opinion about the treatment changed during the program?" (c) "How satisfied are you now about the treatment that was given to you?"Beside a baseline measurement, follow-up data are gathered at two short-term intervals and two long-term intervals. Short-term follow-up measurements are at 5 and 10 weeks after randomization. Long-term follow-up measurements are at 6 months and one year after the end of the intervention, respectively. At every test moment, participants fill in a compound questionnaire on a stand-alone PC, and they undergo an isometric back strength measurement on the lower back machine. The content of the questionnaire varies per test moment: parts of the questionnaire referring to potential prognostic variables  are only displayed at baseline, and at 6 and 12 months of follow-up. Figure Double blinding or placebo control is virtually impossible in trials that involve treatment modalities like the ones used in this study, since both patient and provider are inevitably aware of the content of the treatment.Because our physiotherapists are aware of which treatment they provide, there is always the possibility that they may inadvertently convey different expectations to the patients in each treatment program. This could enhance non-specific effects in either of the two groups. Therefore, as mentioned, beliefs and attitude of the physiotherapists towards back treatment in general are evaluated at baseline, as well as at the end of the study period.Another limitation of trials comparing a relatively new treatment to the usual care is the risk of a potential nocebo effect; i.e. patients might feel disappointed after being allocated to the standard therapy. To minimize this effect, both programs are introduced to the patient as potentially equally effective treatments in restoring back function, with the relative efficacy of both programs as the main focus of the study. Moreover, at baseline patients are informed about the opportunity they have to continue with a treatment modality of their choice (e.g. our training device) after finishing the treatment period. Patient satisfaction with the allocated treatment is measured directly after the treatment period.Other efforts to achieve a certain level of blinding within patients, physiotherapists, and data researchers, are:• low back strength training and measurement are done as much as possible by two different physiotherapists;• an independent data manager collects data from all study locations, and recodes patients and locations to unique codes before handing the database to the researchers.We attempt to enroll 200 patients at the four military health centers, i.e. 100 patients per treatment group. According to power calculations (α = 0.05 and 1-β = 80%), this sample size is sufficient to detect a 20% difference in our primary outcome measure Global Perceived Effect, between the BS and UC program. In our beliefs, a 20% difference reflects a clinical relevant change in health status.Statistical analysis will be performed according to the intention-to-treat principle; i.e. patients will be analyzed in the treatment group to which they were randomly allocated. In addition, a per-protocol analysis will be performed, in which only patients with no major protocol deviations will be analyzed. Comparing these analyses with the results of the intention-to-treat analysis will indicate, to what extend protocol deviations and lack of compliance might have biased the results.In our analyses, we will compare the size of the effect, if any, of isolated back strengthening and of usual care for the low back on our primary and secondary outcome variables. Further analysis will determine whether several potential prognostic variables will influence the magnitude of the treatment responses, and if subsets of patients can be distinguished that can be indicated as good-/bad-responders to our specific back training. Demographic and clinical characteristics, as well as baseline outcome measures will be summarized by descriptive statistics. Longitudinal multilevel analyses will be used to examine differences in all continuous outcome measures at 5 and 10 weeks after randomization, and 6 and 12 months of follow-up.In order to obtain full commitment from the participating military health centers, as well as to make sure that every center uses the study protocols in the same way, we organize several feedback and feedforward sessions with all participating physiotherapists. In these sessions, we explain different aspects of the trial design, give instructions on the test and training protocols, and answer remaining questions.After these sessions, we install the required equipment  at the four locations. Each center has a practice period of about 8 weeks to become familiar with the instruments, logistics and protocols, by means of ad hoc training and test sessions with non-participating (regular) back patients. Our researchers join these sessions and, if necessary, give correcting feedback during and after a test or training.After this practice period, each location officially starts with the study. Once every two weeks, our researchers visit the centers to monitor progress in recruitment and data handling, and to observe the execution of test and training sessions.This article describes the rationale and design of a multicenter randomized controlled trial in which the efficacy of a specific type of lumbar extension training and usual care are compared in patients with nonspecific LBP longer than 4 weeks. A substantial number of trials have been conducted that included lumbar extension training in low back pain patients ,12,32,33Our population at risk can be seen as a selected population of mainly male employees, who work in a dynamic organization with a strong culture of physical fitness. We realize that this selection might limit the external validity of the outcomes of this study. However, results of the trial may be extrapolated to other working populations with a more-than-average degree of physical straining job activities, e.g. policemen and firemen on duty or construction workers.Besides, despite the "fit-and-healthy" image that soldiers have in our society, a large health survey among a cross-section of male military personnel of 30–40 years showed no favorable scores on several cardiovascular and fitness parameters in comparison to other populations of Dutch men ,35. In tMoreover, for reasons of homogeneity it might be even an advantage to only have a study population of working men with (probably) moderate low back trouble in this study.We hope with this trial to give greater insight to caregivers within and outside the RNLA on treatment options for workers in the sub-acute or chronic phase of their LBP. If, for instance, our minimal intervention approach is equally or more effective than the usual care, medical decision makers may consider implementing this treatment modality in the daily practice of the physiotherapist, by weighing the costs  and benefits (e.g. reduction of treatment time).RNLA = Royal Netherlands ArmyRCT = randomized controlled trialLBP = low back painBS = Back Strength interventionUC = Usual Care interventionrep = repetition on back extension machineThe authors declare that they have no competing interests.The pre-publication history for this paper can be accessed here: