The process of identifying differentially expressed genes in miroarray studies with small sample sizes can be improved substantially by extracting information from a large number of datasets accumulated in public databases. t-test analysis with five samples in each group or to that of a regularized t-test analysis with three samples in each group. Our results are further improved by weighting the results of our approach with the regularized t-test results in a hybrid method.We demonstrate that the process of identifying differentially expressed genes in microarray studies with small sample sizes can be substantially improved by extracting information from a large number of datasets accumulated in public databases. The improvement comes from more reliable estimates of gene-specific variances based on other datasets. For a two-group comparison with two arrays in each group, for example, the result of our method was comparable to that of a  Microarray experiments are often used to identify potentially relevant genes in biological processes. By determining which genes are differentially expressed between different states, for example, hypotheses can be developed as to the role of those genes in the underlying biological mechanism -4. HowevOverall, the need for a large sample size is acute for expression profiling studies. The number of arrays needed in a study depends on many factors, including the study design, the magnitude of biological variation in the samples, technical variability introduced in the experiment, and the desired level of sensitivity and specificity for differential expression. Several studies have examined this issue. A model with additive and multiplicative noise was used to derive the number of samples necessary for detecting fold changes of given magnitude when false-positive and false-negative rates are specified . The dift-test, although other similar statistics such as the signal-to-noise ratios [p-values for multiple testing [In the context of finding differentially expressed genes, the null hypothesis for each gene is that it is not differentially expressed between two groups, usually against the two-sided alternative hypothesis that the gene is up- or downregulated. The most commonly used statistical test in this setting has been the two-sample e ratios  have oft testing  and the  testing . Ideally testing , but in  testing . The mett-test or variations thereof is crowded by a large fraction of genes for which large t-statistics are due to underestimation of variance by chance.A fundamental difficulty in drawing reliable conclusions from a small number of samples lies in accurate estimation of the gene-specific variances, or the variance of a difference in mean expression levels per gene, with which to determine the statistical significance of observed changes in expression. Because variances based on a very small number of samples tend to fluctuate wildly as a result of randomness in sampling from a population, our ability to assess differential expression is drastically impacted. A naive application of standard methods used for larger sample sizes can result in a large number of false positives for differential expression. For example, with a small sample size, the list of significant genes identified by the t-test. A Bayesian framework for combining the variance estimate with a background variance associated with neighboring genes was developed in [Many methods have been devised to address this problem. A popular approach has been some type of regularization of the loped in ; a metholoped in . In the loped in ; empiricloped in -17. Nonploped in , analysiloped in , and Bayloped in ,21 are aloped in .Whereas all the available methods attempt to improve the identification of differentially expressed genes essentially by gathering information across similar genes, we suggest another solution. We propose estimating the natural variance of individual genes using a large number of experiments performed previously. This provides a different and potentially more stable and accurate estimate of the variance for each gene than by simply looking at the variance of a small number of expression levels, especially in studies with very small sample sizes. Using these variances as the basis for determining differential expression offers an alternative method that can reduce the false-positive rate significantly. As the most effective method, we propose a hybrid method in which we combine the variance estimate from the current dataset with the estimate from previous experiments. This approach can also be incorporated in other settings, especially in a Bayesian framework with prior distribution for variance derived from the database. It can be applied more generally to other testing procedures such as ANOVA that benefit from more accurate estimation of gene-specific variances, and can be easily extended to the estimation of the covariance matrix in multivariate analysis.More reliable calculations of such variances based on many chips is becoming increasingly possible through large public databases of previous experiments. Public databases such as the Gene Expression Omnibus (GEO)  contain t-test, the new GEO-adjusted method, the regularized t-test, and a hybrid method combining the GEO method and the regularized t-test. The primary difference between these methods lies in the denominator of each method's t-statistic. The GEO-adjusted method replaces the sample variance estimate in the denominator with the gene-specific variance calculated from the GEO database . Hence, the genes are sorted using the modified t-statistic:We compared the performance of four methods in accurately assessing differential expression of genes: the standard μi1, μi 2are the means for the groups 1 and 2, respectively, for the ith gene, n1 and n2 are the sample sizes in the groups 1 and 2, and σ2 GEO,1 is the gene-specific variance from the GEO database.where t-test, ranking genes based on the modified t-statistic:The regularized method we used added a small constant to the denominator of the σ0 is the fifth percentile of all variances . The reFinally, we introduce a hybrid algorithm that combines the GEO method with others through a voting mechanism. This provides a portable solution that can be combined with a variety of other testing procedures and could potentially improve the performance of any other algorithms designed to determine differential expression in experiments with small sample sizes.t-test analysis for the full dataset as the master list; with a sufficiently large dataset, this master list is a close approximation to the true list. Thus, we used the large dataset to compute a true t-statistic for each gene and then treated random small subsamples of the arrays from the dataset as simulated observed datasets from which we could compute estimated ranks for small subsamples. Because exploring all realizations of possible subsets for a large full dataset would be prohibitively time-consuming , we sampled repeatedly for subsets until we obtained convergent results. We then compared these lists of differentially expressed genes with the master list for overlaps or correlations in the orderings. Once the size of the subsets approaches the size of the full dataset, there can be a substantial overestimation in the overlap of genes, owing to the fact that the master list is generated using the dataset from which the subsamples are derived. However, this effect appears to be negligible in our simulations because of the large size of our full dataset and the small subsample sizes that are of our interest.To compare the effectiveness of the methods, we determined lists of differentially expressed genes in order of significance by applying each procedure to a large number of subsets of arrays of a given size. These genes were then compared with the 'master' list of differentially expressed genes to assess the accuracy of the method. Because we generally do not know the correct ordering of genes with differential expression, we substituted the list obtained by the The dataset primarily used for testing was a prostate cancer dataset  that hadt-test was compared to the GEO-adjusted method. The behavior of the correlation coefficient was tracked as the number of genes being analyzed was increased and the averaged values over many simulations are shown in Figure t-test as the sample size increases, and that the results of GEO tend to correlate better with the master list than the results of 2v2, 3v3, 4v4, or 5v5 t-test.The first measure that was used to assess the effectiveness of the GEO-adjusted method was the correlation between the rank of the top genes returned by various methods and the true rank of those genes. This method was also used in . In thist-test at determining differentially expressed genes in small sample sizes. Compared to a simple t-test, the GEO method performs substantially better, returning results from a 2v2 test that are comparable to the results returned by a 5v5 experiment using t-test. Using GEO variances on a 2v2 test returns 231% more of the top 50 genes than the unadjusted t-test. While we are not suggesting that a simple t-test is a recommended method of assessing differential expression in such small sample sizes, it illustrates the potential of this method. Using gene-specific variances developed from GEO databases is clearly more accurate than the variances that an uninformed t-test derives from small samples. We do not plot the error bars for each measurement in the figures owing to space constraints, but we have verified in the important cases that the separation between the curves is significant.To further assess the reliability of the results, tests were conducted to determine the number of top 50 genes from the master list that were accurately returned using various methods. In Figure t-test. By smoothing out the variance estimates, the regularized t-test returns a more accurate assessment of differentially expressed genes than the standard t-test. Thus the gains from the GEO method over the regularized t-test were less substantial than over the standard t-test but still significant, especially for shorter gene lists. Improving our ability to reliably detect the differentially expressed genes with a short list is generally more valuable than doing so with a longer list simply because these genes at the top are the ones that an investigator examines most closely. As shown in Figure t-test in those three areas  was more than 30%. The performance of GEO on a 2v2 analysis seems roughly comparable to the performance of the regularized t-test on a 3v3 sample analysis.The GEO-adjusted method also compared favorably to a regularized t-test and the GEO method both use different, yet effective, techniques to smooth out variance, they can both contribute to the differential expression analysis. By using a voting method that weights and averages the results returned from the regularized t-test and the GEO method, the performance improves further . The results of a 2v2 chip analysis using our voting method nearly match the performance of a 4v4 regularized t-test analysis, which is quite promising /((x + y)/2); and z-score based on local variance correction  across signal intensity, as implemented in SNOMAD [t-test. The method based on the z-scores performs slightly better than either of the standard methods, but GEO still returns 57% more of the top 50 genes. In the 1v1 case, the voting method proves useful, improving the results of both methods. By combining the z-score method and GEO's rankings, the results are superior to a 3v3 regularized t-test analysis. The voting method captures 83% more of the top 50 genes than the best of the standard methods. These results reflect the success of the voting method in combining GEO's rankings with a variety of other methods to significantly improve the overall performance.Tests were also performed on other sample sizes, namely 1v1 and 3v3. Although we view the first case especially as an inadequate design and do not recommend it, we have found that investigators are sometimes forced to perform analysis on such a small number of samples. We are therefore interested in improving the effectiveness of such exploratory analysis, the results of which must be verified using other techniques such as quantitative reverse transcription PCR (QRT-PCR). In our 1v1 analysis, we compared the GEO method to three methods of ordering genes on the basis of differential expression: fold ratio, n SNOMAD . Basic ft-test and GEO method were also compared on 3v3 comparisons. Whereas GEO still returns more reliable estimates than the regularized t-test, the improvement is smaller than in the case of the smaller sample size comparisons. In the 3v3 case, the GEO-method results are comparable to those of a 4v4 regularized t-test, returning 17% more of the top 50 genes than the 3v3 regularized t-test. However, we do find that the voting method again improves the results, returning very similar numbers of correct genes as a 5v5 regularized t-test . Because two samples capture a much higher percentage of the data in 11 chips than in 50 chips, we expect the usual tests on subsamples to naturally provide results more similar to the master list. Therefore, we expect to see less of an improvement from GEO than in our cancer dataset. As before, we see the GEO results consistently providing better results in the smaller sets of genes than the standard e Figure  and 40-1e Figure . While tt Figure . In the For this method to be successful, a significant number of previously run chips must be available. As public databases grow in size and number, this limitation will gradually diminish, but not all chip types currently have enough available chips to use this method. Whereas the most popular chip types (such as Affymetrix HG-U95A) have hundreds of previously run chips available, it is more difficult to find databases of the less popular ones. In an attempt to test for the number of chips sufficient to utilize this method, variance analysis was performed. In Figure t-test. If our gene-specific variances were based on even more reliable estimates (such as samples from the same tissue or same disease), the performance of the GEO method would probably be increased. As public databases grow in size and organization, this should become increasingly possible.When trying to estimate the gene-specific variances for a particular experiment, the best approximation would come from a database of similar experiments. Because gene expression profiles have the potential to vary widely in cell and tissue type, examining many other chips of the same tissue type should provide the best indication of the baseline variance. For example, it would make most sense to draw on a large database of cancer chips to derive relevant information for a cancer dataset. Unfortunately, because of the dearth of large datasets that match each other in tissue type, chip type, and post-processing, it is difficult at this time to test this theory. Because our public databases do not yet contain enough chips sorted by tissue type to perform this procedure, we are forced to mix all the chips of any given type together. Yet, even with only a database of totally unrelated chips, we still saw a significant increase in performance, even over already improved methods such as the regularized We have shown here how to derive more stable variances based on chips of the same type. The problem is much more complicated when multiple chip types are involved. In fact, we have observed that even different generations within the same platform do not give concordant results. When the same tissue samples were hybridized on both HG-U95A and HG-U133A chips, the dominant feature in the data was the chip type rather than the sample characteristic, and the lists of differentially expressed genes differed substantially between the two cases. Standardizing across these two types can be done for a portion of the genes but it is an involved process . Efficiently combining data from single-channel and double-channel arrays is even more difficult. A more comprehensive database with a larger number of arrays spanning a greater variety of experiments would alleviate the problem to some extent, but methodologies for integrating data from multiple platforms will be essential, not only for better estimation procedures for differential expression but for other purposes as well.Public databases are an important resource for investigators to consider. With the stores of chips accessible online, valuable information concerning genes can be compiled and used to supplement new studies and avoid duplication of effort. This methodology would be improved by modification to the databases. Mainly, it is very important to start gathering the raw files instead of processed files. With Affymetrix chips, for example, .cel files should be stored, so that they can be processed using the latest methodology and maintain their usefulness. Already, many of the chips in the GEO database are less useful because they only report values processed through MAS 4.0, an outdated methodology, and comparing these with values generated through MAS 5.0 introduces another source of variation. In addition, the chips should be categorized and sorted according to tissue type, to further facilitate grouping and analysis. These modifications would improve the ability to use previously run chips, thus countering the high costs associated with microarray experiments and enabling the sharing of information to accelerate progress. Thinking about how to take advantage of these databases could provide further improvements to methodologies and enable more tools to be used to study gene functions.This work proposes that value lies in pooling information from previous studies. Specifically, gene-specific information can be collected from public databases housing many chips, supplementing new studies and ensuring more reliable results. We show that compiling information from databases provides us with a different and potentially more accurate estimate of gene-specific variance, improving our differential expression analysis in small samples. In addition, because this improvement seems largely independent of the method of analysis, we are able to combine it with regularization in a voting method, leading to superior results. There were particularly strong improvements in the identification of the smallest groups of most differentially expressed genes, which would probably be deemed most important by an investigator as they are easiest to validate. Overall, the scale of the improvement is significant, as it allows investigators to halve their costs in some cases and still retain similar accuracy. The same approach can also be formulated in other settings, especially in the Bayesian framework in which priors for the gene variances may be estimated from previous datasets. Furthermore, as public databases are steadily growing in size, we expect refinement of this method to deliver greater success in the future. Regardless of what method an investigator might use, public databases are clearly a useful source of information and should prove useful in supplementing microarray studies.Because the very nature of public datasets implies that many of the chips have been generated and processed in different manners, standardization of the data is paramount. To maintain comparability, the chips were filtered to remove any chips processed with an algorithm other than MAS 5.0. After removing other unusable chips  471 HG-U95A chips remained.Normalization of all of these chips is crucial, in order to guarantee that scales are similar. In an effort to preserve the general characteristics of each chip, conforming their scales while allowing for some chip-by-chip variability, experiments with multiple methods of normalization were carried out. The two major types included normalizing the trimmed mean and trimmed variance of each chip and using percentage ranks instead of numerical expression levels. In the first case, all of the data points were adjusted to align the mean and variance of the middle 90% of values. In the percentage ranks method, the values were assigned percentiles, removing most normalization effects. In addition, a scale was generated that related the percentile with the average rank change of that percentile. The average rank change for a gene in the middle of the scale was significantly larger than the average rank change at either extreme. This scale was used to adjust the variances on the basis of the rank. Because the results from both normalization methods were fairly similar, only the results of the trimmed mean, trimmed variance experiments are reported here.After all of the chips were normalized, the gene-specific variance was calculated. These variances were calculated in two separate ways, using a global variance and a pooled variance:xij is the expression level of array i in experiment set j;  the mean in the experimental set j;  is the mean in all arrays; D and Dj contain the indices for the experimental sets and the arrays in the jth set, respectively. The global variance tends to reflect the degree that a gene may vary between different tissue types and diseases while the pooled variance reflects the degree that a gene tends to vary within each experiment. The global variance proved slightly more effective in the cancer dataset, while the pooled variance was more effective in the muscular dystrophy dataset. This seemed to be correlated to the composition of our GEO background datasets. Our set of 471 GEO chips contained 210 cancer chips but only 42 muscle chips. Because a large proportion of the total chips were cancer chips, a global variance may have more accurately represented the information in the whole dataset. However, because so many of the GEO chips were non-muscle, readjusting them into a pooled variance format may have provided a better gene-specific assessment of general expression. We further filtered the variance calculations to eliminate artifacts created by improperly processed chips along with biases from experimentation . Thus, the highest and lowest 10% of values for each gene across the full set of GEO arrays was trimmed off for the variance calculation. The 10% parameter was chosen experimentally, by tracking how stable variance calculations were as various percentages were trimmed.where, for each gene, N asymptotically. Because the GEO data are an aggregate of many experiments under different conditions often processed differently, we cannot assume the same underlying distribution in general and hence we do not know if the estimators necessarily approach the true variance. However, these estimators appear to be reasonably good approximations to the 'true' variance as demonstrated by the numerical results, and they certainly perform better than estimates based only on the current data.The statistical properties of these variance estimators are difficult to show rigorously. If the samples from the GEO datasets can be assumed to come from the same population as those in the current study, the estimators should be unbiased and the proposed test statistic should behave as t-test analysis. Then, the various methods were compared with each other through a process of subsampling to determine how accurately the results reflect the master list. After two samples from each group were randomly selected, all the genes were filtered out that did not have an expression level above 100 in any of the samples. The goal was to lower false positives among the non-GEO methods, as their results could easily be influenced by small expression levels that by chance ended up with virtually no variance and thus were assigned large t-statistics. After processing in this way, the top genes derived using the t-test, the regularized t-test, and the GEO-adjusted method were compared with the master list to determine their effectiveness. This subsampling procedure was repeated 500 times for each experiment, and the results were averaged. These methods are outlined in the Results section.A master list of the most differentially expressed genes in the dataset was determined by t-test and the regularized t-test, the greatest success was found by averaging the results of the regularized t-test method and the GEO method. By averaging the ranks that we receive using GEO and using the regularized t-test set, our results are improved concerning our most important genes. This is not seen when the results of the simple t-test and GEO are combined, because the lists produced by the simple t-test are simply too inaccurate. However, as GEO and regularized t-test produce lists that are similar in quality, yet different in nature, a boost can be obtained by averaging the lists. Because using just the GEO variances ignores some of our experimental data and using just our experimental variances ignores global data, it seems that an averaging or voting procedure is a superior way to optimize results. In particular, the system that we used averaged 75% of the value of the lower rank (nearer the top of the list) with 25% of the value of the higher rank. A final score was obtained by combining the results from each method in this way, and the genes were re-ranked on the basis of this score. By using the 75%/25% ratio, genes that have a particularly high ranking on one of the methods are given slightly more importance than genes that have average rankings in both methods. Empirical testing of a number of combinations showed that the 75%/25% combination returned superior results, although all combinations experimented with returned results that were better than either method alone.Although the GEO-adjusted method was superior to both the


It provides an excellent elementary introduction to this topic.Following an illustrative historical introduction, the author briefly reviews vascular physiology. This is followed by the basics of fluid mechanics as an introduction to the hemodynamics of large arteries. A dedicated chapter illuminating the dynamic consequences of vascular branching follows this chapter. This is the field to which Professor Li has made his substantial contributions.The following chapters cover the venous system and microcirculation. Finally the book reviews measuring techniques used to study hemodynamic behavior.The author suggests this volume to be "a companion" to his own treatise "The Arterial Circulation" . For thoWhile the new book adds useful information on the venous system and on microcirculation, a topic that has been neglected in classical treatments of hemodynamics, this new volume is substantially less comprehensive in most topics covered in both. Also its index is regretfully, substantially less detailed. Little new has been published in this field since the first book was published in 2000, with the notable exception of Zamir's book "The Physics of Pulsatile Flow" [In brief, this book, which is more affordable than its predecessor, should be regarded as a good introduction to the topic, to be used primarily by bioengineering students, rather than an updated authorative text by its erudite author.


A learning module based around the case of a man with ezema who presents with a rash around his ear and eye. Test your knowledge with our online quiz A 33-y-old man presented to his primary care practitioner with a rash beginning around the left ear and spreading into the periorbital region. He was known to have eczema (atopic dermatitis), and the diagnosis of secondary bacterial infection and periorbital cellulitis was made.Because of a history of penicillin allergy, the patient was started on erythromycin. This treatment had no effect, and the rash extended. On day 4, he presented to the hospital accident and emergency department. He was systemically unwell, complaining of drenching sweats and rigors. On examination he was alert, he was pyrexial at 39.2 °C, his pulse was 100 bpm, and his blood pressure was 128/70 mm Hg. There was a widespread erythematous rash covering his face, chest, and arms, which was described as wet with a yellowish exudate. The rash extended around both eyes, which could not be opened .The patient had a history of atopic eczema (since childhood), rhinitis, and asthma. He was taking inhaled corticosteroids for asthma and had last received a course of systemic steroids one year previously. There were no risk factors for HIV infection.In many patients with a rash, the morphology of the rash will lead to a provisional clinical diagnosis, and it may be sufficiently characteristic for no confirmatory tests to be needed. An example is the typical rash of shingles. There are two broad reasons for doing investigations in a patient presenting with fever and a rash. Firstly, specific tests—such as blood tests, cultures, or a skin biopsy—may be required to help establish the diagnosis. In this 33-y-old patient, the rash was thought likely to be a skin infection, and so the specific tests that were indicated included viral and bacterial cultures. A skin biopsy would have been considered if the diagnosis remained unclear and the patient was not responding to empirical antimicrobial therapy. Secondly, investigations are used to evaluate how ill the patient is and whether there is any organ involvement beyond the skin. In this case, we were most concerned about severe sepsis with a risk of organ failure.9/l ; and differential white blood cell count, 90% neutrophils with a left shift. The patient was hyponatraemic , but renal and liver function tests were normal. C-reactive protein was 140 mg/l . Chest X ray was normal. Blood cultures and skin swabs were taken along with samples for viral culture and polymerase chain reaction (PCR).Investigations showed the following: haemoglobin, 128 g/L ; white blood cell count, 9.9 × 10A provisional diagnosis of bacterially infected eczema was made, and, in view of his history of penicillin allergy, the patient was started on intravenous vancomycin. He was admitted and referred for dermatology, infectious diseases, and ophthalmology reviews.On closer inspection of the rash, it was apparent that there were multiple small vesicles 1–2 mm in diameter and shallow ulcers over the face and periorbital region . There wIn view of the characteristic picture and underlying eczema, the diagnosis was revised to one of severe eczema herpeticum. The patient denied any previous history of oral cold sores or genital ulceration. However, the severe degree of skin inflammation, high fever, raised C-reactive protein, and left-shifted neutrophils suggested co-existent bacterial sepsis.High-dose intravenous aciclovir (10 mg/kg every 8 h) was started. Aciclovir inhibits thymidine kinase, which is an essential enzyme for several herpes viruses. Aciclovir has excellent activity against herpes simplex virus (HSV), and, although less potent, it is also effective against varicella zoster virus [Staphylococcus aureus [This man had severe skin involvement with a high likelihood of complicating bacterial sepsis, which is most commonly due to s aureus . ErythroS. aureus, which was resistant to penicillin, erythromycin, and clindamycin but sensitive to all other agents. Skin and eye swabs also grew S. aureus. HSV DNA was identified by PCR on fluid taken from the face. Viral cultures were positive for HSV-1. Serology taken on admission was positive for HSV-1 IgG.Two separate sets of blood cultures subsequently grew The patient rapidly defervesced, and the vesicles desquamated on day 6 . He was S. aureus. As mentioned above, the eyes were proactively managed to avoid corneal involvement. The S. aureus bacteraemia could have progressed to severe sepsis or led to metastatic spread of infection. Echocardiogram was normal with no evidence of endocarditis, and intravenous vancomycin was continued for a period of 14 d to minimize the risk of metastatic spread. Close attention to infection control procedures is essential to prevent hospital-acquired infection of the damaged skin or intravenous line sites.In the acute stage of his presentation, our two main concerns for this patient were the extent of involvement of the eyes beneath the eyelids and the positive blood cultures for Kaposi's varicelliform eruption describes the widespread dermal infection caused predominantly by HSV-1 in patients with a variety of skin conditions . It is mPrompt use of antiviral therapy is highly effective in controlling HSV replication. Aciclovir is the antiviral agent of choice and is usually given for 7 d. Patients with moderate to severe disease require admission for intravenous aciclovir. Oral aciclovir is effective for mild cases, which can be managed on an outpatient basis . BacteriA proportion of patients may experience recurrent attacks of eczema herpeticum . RecurreA recent retrospective analysis of 100 cases of eczema herpeticum in patients with atopic ezcema highlighted some predisposing factors. The analysis found that patients with eczema herpeticum had developed atopic eczema earlier and had higher total serum IgE levels than control patients with atopic eczema alone . In addiThe rapidly progressive, widespread, crusted papules, vesicles, and erosions in a patient with atopic eczema are characteristic, and an experienced physician who has seen eczema herpeticum before will make a rapid clinical diagnosis. However, some patients present with atypical or purely crusted lesions and no obvious vesicles, making a clinical diagnosis more difficult. Thus, a high index of clinical suspicion is required, and both viral and bacterial cultures are essential when a patient with atopic eczema presents with a spreading vesicular or crusting rash . Rapid cA similar and potentially fatal disease may follow smallpox vaccination ,10. UntiEczema herpeticum is an uncommon but potentially fatal disorder that can present to primary care practitioners or to the emergency department.Diagnostic delay is common and may increase morbidity.First-line therapy is with acyclovir; intravenous high-dose therapy is required in severe cases.Patients should be referred to a dermatologist for specialist care and follow-up to optimise eczema management, so that recurrence is less likely.Intensive nursing care is indicated to minimise scarring and promote rapid healing.If the periorbital region is involved, refer urgently to an ophthalmologist.


They have been implicated in growth regulation and have been shown to be involved in both pre-mRNA and pre-rRNA processing. More recently, however, these proteins have been reported to act as transcriptional co-activators for estrogen-receptor alpha (ERα). Furthermore these proteins were shown to interact with co-activators p300/CBP and the RNA polymerase II holoenzyme. Taken together these reports suggest a role for p68 and p72 in transcriptional activation.In this report we show that p68 and p72 can, in some contexts, act as transcriptional repressors. Targeting of p68 or p72 to constitutive promoters leads to repression of transcription; this repression is promoter-specific. Moreover both p68 and p72 associate with histone deacetylase 1 (HDAC1), a well-established transcriptional repression protein.It is therefore clear that p68 and p72 are important transcriptional regulators, functioning as co-activators and/or co-repressors depending on the context of the promoter and the transcriptional complex in which they exist. AlthougDrosophila maleless (MLE) gene product . After treatment with RNase/DNase, lysates were fractionated on a Pharmacia Superose 6 HR column in 50 mM Tris-HCl (pH7.5), 150 mM NaCl, 10% glycerol and 1 mM benzamidine, using a Pharmacia AKTA FPLC system. 0.5 ml fractions were collected and alternate fractions were analysed by western blotting. Molecular weight standards from Pharmacia were used to calibrate the column.Fleur de lys substrate, which contains an acetylated lysine side chain (Biomol) and was performed according to manufacturers instructions. Antibody-bound beads were washed in HDAC assay buffer prior to being added to the 96-well plate, to remove immunoprecipitation buffer. Reactions were incubated for 30 min at 37°C with or without the addition of 1 μM TSA. Samples were excited at 360 nm and emitted at 460 nm and were read in a fluorometer. Typically each assay was performed 3 times.293 cells were transfected with either pSG5-myc vector, pSG5-p68-myc, or pSG5-p72-myc. Cells were lysed in buffer B 48 hr after transfection. The lysate was then diluted in buffer A and myc-tagged proteins immunoprecipitated with 9E10 (myc epitope) antibody as described above. The HDAC assay employs BJW carried out the transcriptional and HDAC activity assays, the deletion mapping and the gel filtration, GJB and SMN carried out the co-immunoprecipitation experiments, DJG carried out the original experiments showing that p68 and p72 could act as transcriptional repressors, and NDP and FFP participated in the design of this study. FFP co-ordinated the study and prepared the final draft of the manuscript. All authors read and approved the manuscript.


Citizens increasingly use email in personal communication. It is not however clear to what extent physicians utilize it for patient communication. Our study was designed to examine physicians' activity in using email and to estimate the proportion of email messages missing from documentation in electronic patient records (EPR).All physicians  at the Finnish Student Health Service received a questionnaire by email, and were asked to print it and keep a daily tally of visits, phone calls and email messages over the study period of one working week (5.5. – 9.5.2003). The response rate was 70%. The data originating from the questionnaire were compared with statistical data from the EPR during the study period.The majority  of doctors reported using email with patients, averaging 8.6 (range: 0–96) email contacts and a percentage rate of "email / visit" 20% (range: 0–185%) in one working week. Doctors in the capital city region and those doctors who had a positive attitude toward email for patient communication were most active in email use. Up to 73% of email contacts were not documented in the EPR.The activity in using email with patients verified among Finnish physicians is compatible with recent study results elsewhere. The notable proportion of un-recorded email messages establishes the need for an electric communication system built into the EPR to improve the quality of patient care and to limit medico-legal risks. Citizens increasingly use email in personal communication . It is nInternational and national recommendations and guidelines have been published on email use between doctor and patient; the contents of the Finnish guidelines are well in line with European guidelines ,8. TheseUse of email between doctor and patient has been studied in one controlled and randomized and three cross-sectional studies ,5,9,10. Among Finnish citizens of working age young adults are the most active users of email and Internet ,11. Univfirstname.surname@yths.fi. Principles of communication by email with FSHS' employees and of other forms of electronic services  are available at the FSHS' website.The Finnish Student Health Service (FSHS) provides primary health care services to approximately 140.000 university students in Finland. The FSHS has health stations in 16 university cities. Services include health promotion, consultations with general practitioners and with other clinical specialists, mental health care, and dental care. Since 1993 FSHS has provided health counseling in Internet. Since 1999 all physicians have had an email account at their disposal in health stations and an email address of type: The Social Insurance Institution, the university cities, the State of Finland, and the students themselves finance FSHS services. Students pay an annual obligatory health care fee as a part of the Student Union's membership fee. There is no other fee for preventive services, visits to general practitioner or public health nurse, and laboratory or X-ray examinations prescribed during these visits. Use of Internet services is also free of charge. The FSHS employs 560 persons and 63% of the physicians are general practitioners. In this paper general practitioners also include specialists of general practice/family medicine, whereas "specialists" refers to clinical specialists other than psychiatrists or oral surgeons.The aim of the study was to seek answers to the following questions:1. How actively did physicians at student health care use email in communication with their patients?2. How much did they use email compared to phone calls and patient visits?3. Who were the active doctors using email with patients?4. What proportion of visits and phone calls could be candidates for substitution by email communication?5. Did the volume of visits, phone calls and email messages documented in the EPR of the FSHS during the study period differ from that of visits, phone calls and email messages registered in the study?All physicians (n = 82) in the FSHS' functionary register in April 2003 received a questionnaire by email. We excluded six physicians, who were not any more working for the FSHS and took exception to the two authors. The actual number of survey population was 74. The questionnaire see  includedThe first mailing of questionnaire took place 28.4.2003 and a reminder was sent 5.5.2003. Recipients were asked to print the survey form, fill it in by hand, and return it by internal mail. Overall 52 out of 74 (70%) physicians returned a completed survey.Respondents were grouped according to age, location, speciality licence, and type of employment Table . Facts o®). We collected the numbers of patient contacts documented at Medicus® for the study period using the statistical software Cognos®.All physicians at the FSHS utilize EPR  software. Statistical analyses were conducted using the proportion test for two independent groups, the χ2 test, Fisher's exact test, the unpaired t-test, the Mann-Whitney test and the Kruskal-Wallis test. All tests were made two-sided and p-values below .05 were regarded as statistically significant.We entered data using Microsoft ExcelOf all respondents 29% were men and 71% women .Respondents' general attitude toward email for patient communication was evaluated by the statement "Email contacts with patients facilitate my work." The group of "positives" was formed of the 56% of respondents who on a five step Likert scale replied: "same opinion" or "nearly same opinion."The "positives" reported more email contacts than others . All eleven who had reported more email contacts than phone calls belonged to the "positive" group.Doctors estimated that 2% (57/2296) of patient visits could have been replaced by email. Of phone calls 21% (196/948) could have been substituted with email. Respondents estimated that 10% (45/449) of patients' email messages required a personal consultation.The number of visits registered in the survey did not differ from the presumed number documented in the EPR Table .. The diEven if university students do not represent the whole population, they can act as "pilot population" representing adults of working age of a future information society. Our study population – doctors taking care of students – was small with only 52 respondents. Thus the results of the study cannot be indiscriminately generalized. Because of the small study population comparison of the subgroups may not be reliable.Although the study group was small, it well represented all the doctors at the FSHS, and the response rate was high. A further strength was that we compared the number of patient contacts documented in the questionnaires during the study week to the statistical data of contact numbers from the EPR at the same time. In other studies no corresponding comparison has been made.The doctors were asked to keep a daily tally of visits, phone calls and email messages, and to evaluate how many visits or phone calls could have been replaced by email. Many doctors undoubtedly did this simultaneously with patient work. Some doctors might have been in a hurry, they probably supplemented the questionnaire at the end of the day. To achieve a more accurate evaluation of visits and phone calls replaceable by email, a continuous assessment  could have been stressed even more in the instructions.The doctors at the FSHS do not have a specific electronic communication system focused on patient communication. They use their general, unprotected email system also to communicate with patients. A specific communication system used only for patient communication would enable an automatic collection of the patient communication data and create a more accurate database than our data collection method.Katz and colleagues have made the only controlled and randomized study concerning physicians' use of email . Our ownOur study revealed individual differences in the use of email in patient work. Differences in physicians' activity in using email have previously been reported in only one study . DerivinPhysicians reckoned that email could replace only 2% of visits. This confirms Sittig's evaluation in 2003 that email could possibly cover a small percentage of visits . IncreasWhen we compared contacts in the EPR with contacts registered daily on the questionnaires we found that the majority of email contacts were not registered in the EPR. This finding is supported by Gaster and colleagues who asked physicians themselves to describe how often they usually registered email contacts in patient records .FSHS provides specific electronic services for focused issues . Principles of recommended issues to use email between health providers and patients are available for students at FSHS' websites. We have had a presumption that email messages between FSHS' physicians and their patients mainly handle patient care. Nyström's congress report from 2004 supports our presumption. He explored 139 email messages from 103 individual patients at his GP practice at the FSHS and noticed that 77 % of email messages handled medical tests, and 16 % handled follow-ups of symptoms or illnesses [All university students in Finland have access to Internet and email at their universities. Use of email as communication method in health care does not in their case cause inequalities in health. A general tendency in the societies to provide also health services widely in electronic form (in Internet or by email) can contribute to inequalities for those who are not able to use modern technologies ,17.Doctors at the FSHS had an average of 8.6 email contacts with their patients during one week. The proportion of email contacts per visit was 20%. Physicians estimated that email contacts could substitute 2% of patients' visits and 21% of phone calls. Of email contacts 73% were not documented in the EPR.Our study indicates that email communication really constitutes a part of patient work. This should be taken into account in planning working time and daily timetables. Use of software not integrated with the EPR increases the physician's registering load and currently involves extra work. It is not possible to confirm the patient's identity reliably using two separate systems. A system allowing retrieval of patient's identity safely and with no need to register separately the email communication in the EPR would promote the patient's adequate treatment and reduce the physician's medico-legal risks.There is a need for a larger study on email utilization between patient and physician which better covers the medical profession. The consumer point of view should also be better taken into account. A content analysis of email messages for patient communication combined with assessments of email documentation in the EPR could have strengthened present study regarding the importance of email registration in patient records.In Finland the Ministry of Social Affairs and Health has instigated a major project to safeguard health care . One parThe author(s) declare that they have no competing interests.JC participated in the design of the study, coordinated it, keyed data into computer, performed the statistical analysis and drafted the manuscript with co-authors. MN conceived of the study, participated in the design of the study and wrote parts of manuscript in English. IV participated in the design of study and drafted the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:QuestionnaireClick here for file


Physical exercise has become a cornerstone of management of chronic obstructive pulmonary disease (COPD) because it leads to clinically relevant improvements of exercise capacity and health-related quality of life (HRQL). Despite the scarcity of randomised trials directly comparing exercise protocols, current guidelines recommend high intensity continuous exercise for lower extremities as the probably most effective exercise modality. However, for patients admitted to inpatient respiratory rehabilitation programmes, it is often difficult to initiate such an exercise programme because they are severely limited by dyspnoea and leg fatigue and therefore unable to perform continuous exercise at higher intensities and for periods longer than 30 minutes. Interval exercise may be an attractive alternative for these COPD patients because it allows high intensity exercise with recovery periods. The aim of this study is to assess if interval exercise compared to high intensity continuous exercise is not of inferior effectiveness in terms of HRQL and exercise capacity improvements but associated with better exercise tolerance in patients with moderate to severe COPD at the beginning of a respiratory rehabilitation.We will assign patients with moderately severe to severe COPD to either continuous exercise or interval exercise using a stratified randomisation. Patients will follow 12–15 exercise sessions during a comprehensive inpatient respiratory rehabilitation. Primary end point for effectiveness is HRQL as measured by the Chronic Respiratory Questionnaire (CRQ) two weeks after the end of rehabilitation and secondary endpoints include additional clinical outcomes such as functional exercise capacity, other HRQL measures, patients' experience of physical exercise as well as physiological measures of the effects of physical exercise such as cardiopulmonary exercise testing. Including expected drop-outs, we will need 52 patients per group to show differences corresponding to the minimal clinically important difference of the CRQ. Outcome assessors and investigators involved in data analysis will be blinded to group assignment until analyses have been carried out.Clinicians and the scientific community need evidence on the benefits and tolerance of exercise protocols available in clinical practice. The proposed trial will provide important and needed data on interval and continuous exercise for decision making in clinical practice. Impaired exercise capacity, dyspnoea and reduced health-related quality of life (HRQL) are common complaints of patients with chronic obstructive pulmonary disease (COPD). A major exercise-limiting factor in COPD is peripheral muscle dysfunction characterised by atrophic muscles and reduced fatigue resistance due morphological and metabolic alterations of peripheral muscles As much Respiratory rehabilitation with physical exercise improves exercise capacity and HRQL. AlthoughHowever, data on high intensity continuous exercise come from a trial that included 19 patients with mild COPD who were able to exercise for 45 minutes five times per week during an outpatient programme. For patiA solution to this dilemma may represent interval exercise where paPatients and clinicians will accept interval exercise to treat peripheral muscular dysfunction in COPD only if it is not of inferior effectiveness compared with continuous exercise and if it is indeed associated with better compliance resulting from less dyspnoea and leg fatigue during exercise. There is limited evidence from three randomised controlled trials comparing interval exercise and continuous exercise.-12 A sumThe studies indicated that both interval and continuous training improved exercise capacity, dyspnoea and HRQL and showed insignificant differences between interval and continuous exercise. However, insignificant differences do not allow concluding that interval or continuous are of clinically equivalent effectiveness These trThe investigators did not use steep ramp tests to determine exercise loads but normal incremental exercise tests. For interval exercise, muscle strength and anaerobic capacity is relevant because of the short high intensity intervals, but this is not measured by normal incremental exercise tests. In addition, training load tolerated during interval exercise may be underestimated when normal incremental exercise tests are used.Exercise tests to establish training intensity should consider the exercise mode. Meyer et al. studied interval exercise in several studies -16 in paMeyer et al. also assessed different ratios of work/recovery phases  and found that with these ratios and relatively short phases of high intensity exercise (10–30 seconds), lactate did not accumulate presumably because of lactate elimination during the recovery phases. IntervalBecause of the scarcity of evidence on the comparative effectiveness of interval exercise for COPD patients, additional trials are needed.,6 Our prAll consecutive patients admitted to a teaching rehabilitation clinic for an inpatient respiratory rehabilitation  will be assessed for study eligibility by senior staff physicians. If patients are deemed eligible after exercise testing, which is part of the usual rehabilitation program, senior physicians will inform patients about the study orally and in writing. If patients are willing to participate and provide written informed consent they will be randomly assigned to respiratory rehabilitation with either interval or high intensity continuous exercise. Both groups will perform 12–15 exercise sessions and follow the rest of the rehabilitation programme. Follow-up assessments will be done during, at the end of the rehabilitation programme as well as two and twelve weeks afterwards when patients are back in their home environment.The Ethikkommission of the Kantonsspital Aarau, Aargau, Switzerland, has approved the study protocol.We defined the following in- and exclusion criteria: Patients with COPD as defined by FEV1/FVC < 70% predicted, FEV1 < 50 % predicted after bronchodilation, with or without chronic symptoms  corresponding to a GOLD  stage III-IV and Germ2 < 55 mmHg or no = paO2 ≥ 55 mmHg).A third party not involved in the conduction of the trial will provide online central randomisation . A computerised 'minimisation' procedure will be used to avoid chance baseline imbalances in prognostically important variables MinimisaEvery time the study coordinator has been informed about an enrolled patients, he will enter the randomisation web site enter thSeparating patient enrolment and baseline assessments  from the randomisation procedure (study coordinator not involved in patient enrolment or rehabilitation programme) will ensure concealment of random allocation.The rehabilitation programme will start one day after baseline assessments and study enrolment. Exercise sessions and group lessons will take place five days a week and will consist of daily cycle ergometer training, breathing therapies (30 minutes per day), and guided walking of 15 to 30 minutes. Relaxation therapies (technique according to Jacobson) take place twice a week, patient education  three times a week, smoking cessation advice once a week or more if needed. Apart from physical exercise, the rehabilitation programme of approximately three weeks will be identical for both groups.The target workload for this group will be ≥ 70% of the maximum exercise capacity expressed in Watts and heart rate achieved during the incremental cycle ergometer test. Patients are usually not able to perform high intensity continuous exercise from the beginning and have to adapt to physical exercise. Physical therapists will increase training load as soon as possible to ≥ 70% of the maximum exercise capacity or as high as each individual patient tolerates. In each session , the performed workload (in Watts), if patients reached the target workload (in Watts), adjustments of workload and the requirement for oxygen. We define adherence to exercise as "full adherence" if patients follow at least 12 exercise sessions. We consider the training to be fully tolerated if patients are able to follow the exercise protocol for at least 9 exercise sessions for continuous exercise (taking into consideration the first three exercise session when patients increase training load up to 70% of maximum exercise capacity) and for at least 12 exercise sessions for interval exercise.Previous trials of respiratory rehabilitation or physical exercise did not report any adverse events. Nevertheless, we will record any adverse events such as injuries, cardiac events or increase of respiratory symptoms as they happen during the inpatient respiratory rehabilitation.At baseline and end of the rehabilitation, all patients will perform an incremental cycle ergometer test to the limit of tolerance (symptom based) under the supervision of a senior physician blinded to group assignment. Patients pedal unloaded for three minutes to warm up at 20 Watts. Then exercise load is increased by 7.5 Watts per minute until patients have to stop because of dyspnoea, leg pain, or criteria for stop testing . At the limit of tolerance, we will draw capillary blood samples to measures lactate concentrations and we will set the maximum exercise capacity expressed by Watts. The upper limit for the heart rate during exercise is set as the heart rate measured by the electrocardiogram at the maximum exercise capacity.2 output, minute ventilation, tidal volume and respiratory frequency.During testing, we will record gas exchange and ventilatory variables form calibrated signals derived from rapidly responding gas analyzers and a mass flow sensor. We will record breath by breath the following variables: Pulmonary oxygen uptake, pulmonary COAll patients will perform a steep ramp test at the beginning and end of the rehabilitation programme as described above.In order to characterize the patient included in the study, we will record their age, gender, lung function , co-morbidities such as hypertension, heart diseases, endocrine disorders, chronic rheumatological disorders and psychiatric disorders.The randomisation code will not be broken  until a draft of the manuscript has been written. The authors will write two versions with alternative possible allocation patterns to avoid bias in the interpretation of the results. This approach is methodologically rigorous and limits introduction of bias during the interpretation of the data that some of the authors might have. We will Our null hypothesis is that high intensity continuous exercise is of clinically superior effectiveness compared with interval exercise to improve HRQL (δ ≥ 0.5 in CRQ domains scores). The alternative hypothesis is that interval exercise is not of clinically inferior effectiveness compared with high intensity continuous exercise.In the primary analysis, we will calculate the raw difference and 95% confidence intervals between groups in the mean follow-up score for the CRQ domains 2 weeks after completion of the respiratory rehabilitation programme. In an additional analysis, we will adjust for the base-line score and the four stratification variables using an analysis of covariance. We will use independent t-test to compare the change scores between groups.We will also use the confidence interval approach as recommended for equivalence and non-inferiority trials We will Most methodologists and statisticians agree that the boundaries of equivalence should be defined as the minimal important difference and below the differences observed in previous trials comparing active to control treatments.,39 The mWe will repeat the analysis with calculations of raw and adjusted differences for all other clinical and physiologic outcome measures and test for significant differences between groups using independent t-test if data are distributed normally.We will use both intention to treat and per protocol analysis to show equivalence in either case as recommended by others,39,46,47Our null hypothesis is that patients equally experience high intensity continuous exercise and interval exercise as measured by the Exercise Tolerance Questionnaire. The alternative hypothesis is that interval exercise is associated with the experience of less limiting symptoms compared with high intensity continuous exercise.We will use independent t-tests to compare the measures for exercise tolerance  between groups. Again, we will assess the raw differences between groups in the primary analysis and adjust for baseline scores and the four stratification variables in the additional analysis.Factors, which interfere with outcome measures, can distort the results if unevenly distributed between study groups. We use three approaches to control for confounders: First, we use randomisation to allocate patients. Second, we strengthen the randomisation using a computerised minimisation procedure with factors that are likely to influence the outcome measures . Third, we will collect a number of variables at baseline  that may modify the effect of exercise. We will compare the distribution of these potential effect modifiers between groups and statistically assess their influence on the outcome measures with multiple linear regression models.2 * 2 * SD2/DIFF2, where n = the sample size required in each group , SD = standard deviation of the outcome variable, DIFF = size of desired difference between groups. A and B depend on the desired significance level and desired power, respectively.For calculating the required sample size, we use the formula for comparison of 2 means: n = [A + B]We base our sample size calculations on the CRQ. We used empirical data from our previous trial., where wA priori sample size calculations usually provide only rough estimates. Therefore, we will recalculate sample size during the study when we have the data for 30 patients in each group. To this end, we will re-assess the standard deviation of the outcome variables and, if necessary, adjust the sample size accordingly (without breaking the randomisation code).We will implemented a series of measures to ensure high data quality.1. Site investigators will collect the data using standardized forms. All data will be collected and entered into a single database in the Horten Centre by one investigator. A second investigator will validate completeness and accuracy of data extraction by checking 20% of extracted patient data.2. Checklists with all the data to be collected will be provided for physical therapists and physicians.3. Teaching sessions will be held regularly for physical therapists and physicians involved in data collection aiming at robust data collection.4. Investigators meetings will be held monthly, or more frequently if needed, to discuss recruitment of patients, problems in conducting the study, acquisition of data, to check for consistency and completeness of data and for interim analyses.5. E-mail will serve as the first line of non-urgent communication between research team members.6. Monthly reports will be prepared by the principal investigator that will include the number of patients recruited, stage of follow up for each patient, notification regarding missing patient data and queries from data received.In the last 30 years, researchers made great efforts to study the effectiveness of respiratory rehabilitation compared to usual care. The meta-analyses of a recent systematic review[Research in respiratory rehabilitation should now focus on the evaluation of different exercise protocols. When an effective treatment such as respiratory rehabilitation is available, patients and clinicians are not confronted with the decision whether to start treatment or not, but with the decision on the most appropriate treatment. Therefore, clinicians need evidence from pragmatic randomised controlled trials directly comparing different exercise protocols at issue rather than evidence from (explanatory) trials comparing exercise with no exercise or usual care. The propThe evidence generated in the proposed clinical trial will also be relevant for the scientific community. From the 1970s up to the mid-1990s most investigators conducted explanatory clinical trials in order to better understand how and why physical exercise is effective in patients with COPD. After the recognition of its effectiveness the debate on the optimal exercise modality arose. HoweverThere is a need for randomised controlled trials to explore which exercise protocols are most effective for COPD patients. Another topic that has received little attention in respiratory rehabilitation trials so far is compliance to and subjective experience of physical exercise ExerciseBeside the paucity of data on the effectiveness and tolerance of different exercise protocols, there is also a need for trials that are methodologically sound and rigorous. Most of the studies on exercise or respiratory rehabilitation in patients with COPD did not report on details of exercise tests and protocols. In addition, study design related issues that introduce bias such as description of the randomisation procedure, concealment of allocation, sample size calculations or blinding have not been addressed frequently. Therefore, we try to use strong epidemiological methods to minimize bias in our trial.Our study could make an important contribution to the understanding of physical exercise in patients with COPD and have a significant impact on the structure of respiratory rehabilitation and exercise programmes.None declared.COPD = Chronic obstructive pulmonary diseaseHRQL = Health-related quality of lifeCRQ = Chronic Respiratory QuestionnaireHADS = Hospital Anxiety Depression ScoreFT = Feeling ThermometerMP drafted and revised the manuscript. All authors participated in development of research protocols and in the design of the study. MP, CZ and HS resolved statistical and methodological issues. All authors read and corrected draft versions of the manuscript and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Plasmodium falciparum are reported frequently in the East African highlands with high case fatality rates. There have been formal attempts to predict epidemics by the use of climatic variables that are predictors of transmission potential. However, little consensus has emerged about the relative importance and predictive value of different factors. Understanding the reasons for variation is crucial to determining specific and important indicators for epidemic prediction. The impact of temperature on the duration of a mosquito's life cycle and the sporogonic phase of the parasite could explain the inconsistent findings.Malaria epidemics due to Daily average number of cases was modeled using a robust Poisson regression with rainfall, minimum temperature and maximum temperatures as explanatory variables in a polynomial distributed lag model in 10 districts of Ethiopia. To improve reliability and generalizability within similar climatic conditions, we grouped the districts into two climatic zones, hot and cold.In cold districts, rainfall was associated with a delayed increase in malaria cases, while the association in the hot districts occurred at relatively shorter lags. In cold districts, minimum temperature was associated with malaria cases with a delayed effect. In hot districts, the effect of minimum temperature was non-significant at most lags, and much of its contribution was relatively immediate.The interaction between climatic factors and their biological influence on mosquito and parasite life cycle is a key factor in the association between weather and malaria. These factors should be considered in the development of malaria early warning system. Plasmodium falciparum are reported frequently in the East African highlands [Malaria epidemics due to ighlands -6. Immunighlands . Since tighlands -9 to preighlands ,11. Therighlands -20. Howeighlands -27. Woubighlands  found a ighlands . Moreoveighlands  found vaighlands  showed tighlands ,22,24,29The inconsistency of findings from different studies may be due in part to the interaction of weather factors affecting vector abundance and survival, and parasite maturation, key determinants of malaria transmission. Deposition of mosquito eggs, and their maturation into larvae and then into adults, requires aquatic breeding sites, and is, therefore, dependent on rainfall ,31. The Once female adult mosquitoes emerge, they look for a blood meal, and in the process they ingest malaria parasites (gametocytes) with the blood. The feeding frequency of mosquitoes increases with temperature, resulting in increased proportions of infective mosquitoes . The durThese data on the timing of the mosquito life cycle suggest that malaria cases should follow, at defined intervals, periods of increased temperature and increased rainfall. Moreover, because temperature accelerates several steps in the process of mosquito and parasite development, the time lag between the appearance of suitable weather conditions and the appearance of new malaria cases should shorten as temperature rises. Although based largely on laboratory findings, these data suggest quantitative hypotheses about the precise time lag between increases in temperature and rainfall, and increases in malaria cases. At an average temperature of 20°C, the aquatic phase of the mosquito will be completed in about 28 days (five days for eggs to hatch and 23 days for the larva to develop into adult stage); and sporogony is completed in 28 days Table . At thisThe purpose of the investigations reported here is to test these hypotheses using weekly data on weather and malaria cases. Specifically, we used Polynomial Distributed Lag Models (PDL) to determine the effect of weather factors and their lag distribution on malaria in relatively hot and cold environments using a data set consisting of weekly parasitologically confirmed malaria cases collected from health facilities and locally collected meteorological factors in 10 districts of Ethiopia for the years 1990 to 2000.Plasmodium species; the analysis was restricted to P. falciparum. The original data collected on the basis of Ethiopian weeks were normalized to obtain mean daily cases for each Ethiopian week [Microscopically confirmed malaria cases were collected from a health facility in each of ten districts of Ethiopia over an average of 10 years. Each of these health facilities serve people living in the surrounding localities with few exceptions coming from other places. The data were extracted from records of outpatient consultations for the years 1990 through 2000. These data were compiled by residency  and ian week .Daily meteorological data  recorded at the local weather stations nearest to the health facility were obtained from the National Meteorological Services Agency (NMSA) for the same period. The assumption is that the meteorological data from the local weather stations represent the surrounding localities whose inhabitants are served by the respective health facilities. These daily data were collapsed into weekly data to correspond with the weekly malaria cases. The weekly mean for minimum and maximum temperature and the total weekly amount of rainfall were calculated from the daily records.The data set consists of records with missing values for some of the variables . Because of the multiple time lags considered in the analysis (see below), discarding estimates with a single missing value results in multiple records lost for each missing value. To avoid this substantial loss of data, missing values of the independent variables (weather variables) were interpolated by fitting a linear regression using the value from the previous week and a dummy variable for that week. A new variable was created with original values for non-missing data points and interpolated values for missing data points.The daily average number of cases  was modeled using a robust Poisson regression (implemented in Splus), using weekly rainfall, minimum and maximum temperature as explanatory variables in a distributed lag model. The model was:E(Yst) denotes the expected value for the daily average number of malaria cases at site s on week t; ,  and Rt - i are the weekly minimum and maximum temperature and the rainfall i weeks previously; αs and βs represent the intercept and coefficient for time trend (t), which are specific to the site under consideration.where βi.As described in the introduction, biological considerations suggest that the lag between rainfall and associated malaria cases will be different from that between temperature and associated cases. Therefore, lags of 4–12 weeks were considered for rainfall, and relatively shorter lags of 3–10 weeks for the minimum and maximum temperature. The assumption is that changes in temperature and rainfall at a particular time do not have an important influence after 10 and 12 weeks respectively. The overall effect of a unit increase in minimum temperature (for example) is the sum of the coefficients A large number of variables  were introduced for the three weather factors in this model. The efficiency of the coefficient estimates may be affected due to the large number of parameters to be estimated and the possibility of multicollinearity between the lagged weather factors. When lag terms are put in the same model, correlation between measurements of weather on weeks close together will cause a high degree of collinearity that may result in unstable estimates.βi,γi,θi, forcing each of them to take the form of a (separate) 4th-degree polynomial in i. This reduces the number of degrees of freedom for each weather factor from the number of lags considered to five and circumvents some of the difficulties associated with estimation of coefficients for multiple lags, including instability of estimates due to collinearity of the different lags of the same variable. With this model the coefficients for lagged minimum temperature, for example, are assumed to take the form:A polynomial distributed lag (PDL) model  imposes φk is the parameters of the d-th degree (here d = 4) polynomial distributed lag. To estimate the parameters describing the polynomial lag φk equation (2) was substituted into the unconstrained distributed lag model (1) to obtain a constrained polynomial distributed lag model:where The effects of weather factors on the number of malaria cases were distributed over multiple weeks and the separate analysis for each district (not shown) indicated heterogeneity in magnitude and direction of the effects of the weather factors. Districts with similar climatic characteristics were grouped, in order to reduce the effect of random error and to produce more reliable and precise estimates of weather effects. Moreover, this approach will produce more generalizable results within similar climatic conditions. Thus, the districts were grouped into hot  and cold on the basis of altitude and temperature. The hot districts included Diredawa, Nazareth, Wolayita and Zeway; and the cold districts included Alaba, Awasa, Bahirdar, Debrezeit, Hosana and Jimma. Two separate PDL models were fitted to estimate the effects of different weather factors.A basic issue in epidemiological analysis is controlling for the effect of confounding factors. Malaria transmission is affected by different factors and shows a systematic variation over time. To control for other factors that may affect the long-term trend, a time variable was included in the model, which would remove the long-term wavelength patterns, leaving the deviations representing short fluctuations. Since the long-term trend and the numbers of weekly cases vary between districts, an interaction term between the time variable and district (dummy variable) was introduced.Urban areas may have other sources of breeding sites for mosquito not driven by rainfall. To examine the influence of these and other unmeasured factors that vary between urban and rural environments, separate models were fitted for urban and rural cases.P. falciparum cases from a health facility in each of 10 districts over an average of 10 years and meteorological data from local stations in each of the districts. Table The data set consists of microscopically confirmed The effect of rainfall and temperature on daily average microscopically confirmed cases was estimated by lag in the 10 districts grouped into two climatic zones, hot and cold Table . Figure Similarly, rainfall is significantly associated with malaria cases in the hot districts. Compared to the cold districts, a significant and positive effect of rainfall in the hot districts manifests at relatively shorter lags  and remains positive afterwards but declines and becomes non-significant for the longer lags Figure . Much ofFigure In the hot districts, by contrast, the effect of minimum temperature on malaria cases is more complicated. At short lags, its effect is small and non-significantly positive Figure . A signiFigures To test the linearity of the association between the weather factors and malaria cases, a three dimensional relationship between weather factors, lag and the magnitude of effect at each lag was explored  and cold  environments in Ethiopia.The development of malaria early warning systems ,8 to preThe findings are largely consistent with hypotheses based on the relationship between weather factors and mosquito and parasite development. Rainfall is associated with malaria cases in both hot and cold districts with a lagged effect, and as expected, this lag is shorter in hot districts. The effect of rainfall on malaria is linear with saturating effects at higher rainfall levels  and a small increase in temperature substantially shortens the duration of these phases (to 37 days at 17°C). Similarly, the duration of the sporogony cycle will be short with increasing temperatures  correlation between weekly malaria cases and maximum temperature at shorter lags seen in hot districts may be due to its inhibitory and lethal effect on the survival of the parasites in the mosquitoes . The surAs with all observational studies of malaria incidence and weather, a limitation of this study is the likely presence of some confounding factors that may have influenced the number of malaria cases and may have been associated with weather. Existing interventions such as insecticide residual spraying and other methods are routinely applied and were not included in this analysis. The results would have been biased by such confounding factors if interventions were undertaken on the basis of weather, or if they were undertaken on the basis of incidence and their effect was differential depending on the weather. Another minor problem is with the assumption of a finite length for the delayed effect of the different weather factors. However, the lag length was chosen based on the inter-relationship between weather, mosquitoes and parasites Table  and it wWeather factors alone explain seasonal cycles but were not accurate in explaining the magnitude of unusually bad years Figure . This stThe findings are largely consistent with hypotheses, based on experimental data on mosquito and parasite development, about the interactions of climatic factors in determining the strength and lag structure of weather effects on falciparum malaria incidence. In the examined Ethiopian districts, weather-based predictors of malaria incidence are more useful in rural than in urban settings. These key points should be considered in the development of an early warning system for malaria.HDT and ML conceived the study, undertook statistical analysis and drafted the manuscript. AT initiated the study and made data available in collaboration with WHO and Ministry of Health of Ethiopia. JS made major contributions to the study design and statistical analysis. All authors contributed to the writing of the manuscript and approved the submitted version of the manuscript.Three dimensional relationships between weather, lags and magnitude of effect at each lagClick here for file


MONKEY is a new method for identifying conserved transcription-factor binding sites from multiple-sequence alignments. Saccharomyces, we illustrate how the significance of real sites increases with evolutionary distance and explore the relationship between conservation and function.We introduce a method (MONKEY) to identify conserved transcription-factor binding sites in multispecies alignments. MONKEY employs probabilistic models of factor specificity and binding-site evolution, on which basis we compute the likelihood that putative sites are conserved and assign statistical significance to each hit. Using genomes from the genus  Different types of genomic features have characteristic patterns of evolution that, when sequences from closely related organisms are available, can be exploited to annotate genomes . Methodsbona fide targets of the transcription factor  as follows:Every observed score is a sum of c represents a column in the alignment, and the sum is over all 4n possible columns an alignment of n sequences. The probability distribution function (PDF) of scores is Pw(S), and from this the cumulative distribution function (CDF), the probability of observing a score of S or greater, can be directly computed. Although in principle we can compute the probabilities to arbitrary precision, because the time complexity increases with the number of possible scores, we limit the precision to within approximately 0.01 bits.For aligned sequences, p-values from 5,000 pairs of sequences evolved in a simulation  with those computed by this method, and shows that they agree closely. We have used this method to compute the CDFs for alignments of up to six species, and therefore can apply our method to most comparative genomics applications. We note, in addition, that the likelihood ratio scores are approximately Gaussian (data not shown). As the means and variance of the scores under each model can be computed efficiently  we can estimate p-values using a Gaussian approximation  to ps + w + (a + b), where a and b are the number of gaps in the aligned versions of sequences r and s in position p to p + w, where p is the position in the alignment of pr. For each subsequence of length w in the window, we calculate the percent identity to the reference sequence, and create an alignment of pr to pr + w (in the reference sequence) to the most similar word in the window of each other sequence. This locally optimized alignment is then scored. Note that if a and b are zero , no optimization is done. If a is too large (in most contexts greater than five) we exclude that region of the alignment from further. This heuristic encapsulates the idea that too many gaps are indicative of lack of constraint, but conservatively allows for a few gaps due to alignment or sequence imperfections.The idea is to assign a poor score to regions of the alignment with a large number of gaps, but to locally realign regions with a small number of gaps to identify conserved but misaligned binding sites. To do this, we scan along the ungapped version of one of the aligned sequences - the 'reference' sequence. For each position in the reference sequence Saccharomyces cerevisiae have recently been published and become models for the comparative identification of transcription factor binding sites [S. cerevisiae genes to their orthologs in S. paradoxus, S. mikatae, S. bayanus and S. kudriavzevii genomes using CLUSTALW  and sought to evaluate the effectiveness of MONKEY under different evolutionary models and distances.The genome sequences of several species closely related to the budding yeast ng sites ,11. We aS. cerevisiae genome could be divided into two reasonably sized sets: those known to be bound by the factor (positives) and those known not to be bound by the factor (negatives). Unfortunately, even in yeast, the number of such cases is limited. For many factors we can identify true positives by combining high- and low-throughput experimental data that supports the hypothesis that a particular position in the genome is bound by a given factor. A true negative set, however, must be constructed on the basis of lack of evidence that a sequence is functional, as the interpretation of negative results almost always is ambiguous. In the case of transcription factor binding sites this is particularly problematic, because DNA-binding proteins have overlapping specificity, and we may therefore observe conservation of a binding site because it is bound by another factor with similar specificity. After evaluating all factors with binding specificity in Saccharomyces cerevisiae Promoter Database (SCPD) [Ideally, we would use several diverse transcription factors with known binding specificity, where the set of matches to the factor's matrix in the e (SCPD) , we focubona fide binding sites, we calculated the p-values of the positive and negative sites for each factor, using MONKEY on alignments of all five genomes for Rpn4p and four species (with S. kudriavzevii excluded because too few sequences were available) for Gal4p. We compared the performance of MONKEY with the HB model to scores from S. cerevisiae alone and to a 'simple' score  that utilizes all the comparative data without an evolutionary model.To evaluate the performance of our evolutionary method in correctly identifying p-values to real sites (positives) and high p-values to spurious sites (negatives), and we therefore compared the p-values assigned by monkey based on the HB model to those based on the 'simple' score. Not surprisingly, both methods were a great improvement over searching in S. cerevisiae alone. Overall, when compared to each other, the HB score assigned lower p-values to the binding sites more often in the positive sets  and less often in the negative sets  than did the simple score. We note that some of the supposedly functional Rpn4p sites were assigned higher p-values in S. cerevisiae alone, suggesting that they are not in fact conserved; these will be discussed below.The results are summarized in Table p-values to increase over evolution. To explore the change in p-values over evolutionary distance, we scored the functional and nonfunctional sets of binding sites at a variety of evolutionary distances by creating alignments of different combinations of species . The median p-value of the positive set of TFBSs decreases monotonically with evolutionary distance, with the rate of decrease an approximately constant function of evolutionary distance  or background model (HKY), representing functional and nonfunctional binding sites, respectively . The expected p-values with different combinations of species to be primarily a function of the evolutionary distance spanned by these species, there will also be effects related to the number of species and the topology of the three. For example, in the limit of very long branch lengths, the evolutionary p-values are on the order of the power of the number of species and are independent of evolutionary distance. In contrast, in the limit of very short branch lengths, the evolutionary p-values depend only on the distance spanned by the comparison, as most of the information provided by additional species is redundant. However, because most comparisons that are actually carried out are far from either of these extremes, we sought to evaluate the effects of species numbers and tree topology for the Saccharomyces species analyzed here.The comparisons at the different evolutionary distances used in Figure p-values for all the distances analyzed in Figure First, we recomputed the expected S. cerevisiae and S. kudriavzevii is almost exactly equal to the evolutionary distance spanned by S. cerevisiae, S. paradoxus and S. mikatae  to identify our most confident predictions of conserved matches to the Rpn4p matrix. We chose the p-value cutoff of 1.85 × 10-8, which corresponds to a probability of 0.05 of observing one match at that level over the entire search (using a Bonferroni correction for multiple testing). After excluding divergently transcribed genes, there were 56 genes that contained putative binding sites at that p-value. Of 32 genes in our positive set that had sequence available for all five species, 30 had binding sites below this p-value. Of the 28 genes in the negative set for which sequences were available, only three had binding sites below this cutoff. In this  case we have ruled out nearly 90% of the negative set at the expense of less than 10% of the positives.At the distances spanned by all available sequence data, the UFD1) is annotated as involved in protein degradation, and three  have unknown functions.Examining the expression patterns of these genes Figure  allows tFinally, and most surprising from the perspective of comparative annotation, is a third set of 14 genes, including one from our original positive set and three from our negative set, most of which show no evidence of the proteasomal expression pattern associated with Rpn4p Figure . It is ep-values of individual positive Rpn4p sites at different evolutionary distances. While most of the sites follow the trajectory predicted for sites evolving under the HB model, the p-values for four of the positive sites seem to be well-modeled by the 'background' or unconstrained model. This is surprising because we expect these binding sites to be functional, and therefore under purifying selection. One explanation is that some of these sites may have been misannotated as functional. For example, in addition to a nonconserved positive site, the upstream region of REH1 contains another binding site that is a weaker match to the Rpn4p matrix  for comparative sequence analysis capable of functioning on relatively large numbers of related species, and enabled the examination of several important questions in comparative genomics. While most previous approaches to this problem have used heuristics to define conserved and nonconserved TFBSs, with the probabilistic scores and S. cerevisiae  for sequencing multiple closely related sequences. First, there may simply be no extant species at the exact evolutionary distance desired. Second, the quality of DNA alignments is expected to be much higher for multiple closely related species than for more distant pairwise alignments - if alignment errors prevent correct assignment of orthology, conserved binding sites will not be identified. For the factors considered here, the pairwise comparison performed nearly as well as the multiple species comparison well beyond the evolutionary distances at which pairwise alignments are reliable , suggest species . SequencSaccharomyces species. In our search, 41 of 56 (73%) predicted sites were found near genes showing the expected expression pattern, and are therefore likely to be functional. Even at this level of stringency, however, there are highly conserved sequences that match the matrix, but do not appear to be near genes that are regulated by Rpn4p. It is very unlikely that these sites are conserved by chance. One possible explanation for this high degree of conservation is that these are functional sites, but that the expression of these genes is not accurately detected in high-throughput assays, or their function has not been accurately determined. A more likely possibility is that these sites are conserved because they perform other, unknown functions. Consistent with this hypothesis is the fact that many of these matches fall near other highly conserved sequences  we have also found nonconserved examples among the TFBSs in the SCPD database , all of which have at least some direct experimental support.In addition to the conserved sequences that are unlikely to represent d Figure . Once agCis-regulatory changes have been proposed to be an important source of genetic variation [Drosophila melanogster and D. pseudoobscura .Another potential explanation is that these binding sites are actually conserved, but were not aligned correctly. While this is difficult to rule out in general, in the few nonconserved cases for Rpn4p at least we could not find (by eye) errors in the alignments. Most interesting, of course, would be the situation where these nonconserved binding sites are not due to some error on our part, but rather represent a biological change in the functional constraints on these sequences, possibly resulting in a change in the regulation of the expression of these genes. Our results represent an upper bound on the number of TFBSs for which this has occurred. ariation . Gains aariation ,39, and vice versa. Our results suggest that development of methods that model the evolutionary relationships between species and the evolution of the genomic features of interest yield insight into the challenges for comparative genomics.We have developed a method to identify conserved TFBSs in sequence alignments from multiple related species that provides a quantitative framework for evaluating results. The method - implemented in the open-source software MONKEY - extends probabilistic models of binding specificity to multiple species with probabilistic models of evolution. We have found that a probabilistic evolutionary model  that assp-values shown in Figure w were generated according to the average intergenic base frequencies of the S. cerevisiae genome. These were then evolved according to the Jukes-Cantor substitution model, to a specified evolutionary distance. Likelihood ratio scores and p-values were then calculated for each of the pairs of sequences using the method implemented in MONKEY. Finally, all pairs of sequences were ranked by their scores, and the rank divided by the total number of pairs was taken as the empirical p-value.To generate the empirical S. cerevisiae genes to their orthologs in S. paradoxus, S. mikatae, S. bayanus and S. kudriavzevii by taking the 1,000 bp upstream of each gene, identifying the corresponding region from the other species using data in the Saccharomyces Genome Database [S. cerevisiae coding sequence. We used this strategy rather than simply aligning intergenic regions to control for differences in alignments that might arise from the use of variably sized regions.We aligned the upstream regions of all Database , aligninDatabase  and trimS. cerevisiae background frequencies (ACGT) =  and the median of the branch lengths estimates as the 'background' evolutionary model. The trees with these branch lengths were used as input to MONKEY to calculate p-values. The distances in Figure S. cerevisiae and S. paradoxus (0.194); S. cerevisiae and S. mikatae (0.403); S. cerevisiae, S. paradoxus S. mikatae (0.477); S. cerevisiae and S. bayanus (0.559); S. cerevisiae, S. paradoxus, S. mikatae and S. bayanus (0.816); S. cerevisiae, S. paradoxus, S. mikatae, S. bayanus and S. kudriavzevii (1.090).To obtain estimates of the evolutionary distance spanned by each comparison, we ran PAML  on the eRpn4p: we used Rpn4p sites in proteasomal genes [al genes ,43 to bual genes ,31 and cθ is the 'uncentered correlation', a commonly used distance metric for gene-expression data [n, that are available for each gene. All matches to the Rpn4p matrix (S. cerevisiae likelihood ratio score > 9) in the upstream region of a gene that matched the proteasomal expression pattern (t > 8) were considered to be true Rnp4p sites. The negative set consists of all sites that matched the Rpn4p matrix with a score greater than 9, and excluded sites in genes with even weak similarity to the proteasomal expression pattern (t > 0) or that were annotated [where ion data . Our sconnotated  as involGal4p: we used the matrix from SCPD [S. cerevisiae genome with a cutoff equal to the lowest score in the positive set and then eliminated any binding sites near genes that showed evidence for regulation in the systematic studies.rom SCPD   is calculated as above, and we define:where V:We can write a similar expression for the variance, In order to predict the scores for the genes in our positive and negative sets, we are interested in the case were we have observed a match to the motif in one species, but the constraints on its evolution are either those of the background or the motif. We can compute the expected scores under these assumptions as follows:p(Xi|motif) is the single species probability of observing the base Xi at position i in the specificity matrix (f), and using Bayes' theorem:where p and p(Yi|Xi) with p and p and changing the sum over Yi to a sum over all the other leaves in the tree except the reference, in this case, Xi. For the functional set, we assumed the binding sites were evolving under the HB model [This calculation can be extended to the multiple species case, by replacing the distributions HB model , and forS. cerevisiae transcription factors. Additional data file Drosophila melanogaster genome, with the binding sites grouped according to whether the cluster has regulatory activity.Additional data file S. cerevisiae transcription factorsThe fraction of binding sites that are not conserved for several different Click here for additional data fileDrosophila melanogaster genome, with the binding sites grouped according to whether the cluster has regulatory activityThe conservation p-values of predicted binding sites in high-density binding site clusters in the Click here for additional data file