FU is the human homologue of the Drosophila gene fused whose product fused is a positive regulator of the transcription factor Cubitus interruptus (Ci). Thus, FU may act as a regulator of the human counterparts of Ci, the GLI transcription factors. Since Ci and GLI are targets of Hedgehog signaling in development and morphogenesis, it is expected that FU plays an important role in Sonic, Desert and/or Indian Hedgehog induced cellular signaling.FU gene was identified on chromosome 2q35 at 217.56 Mb and its exon-intron organization determined. The human developmental disorder Syndactyly type 1 (SD1) maps to this region on chromosome 2 and the FU coding region was sequenced using genomic DNA from an affected individual in a linked family. While no FU mutations were found, three single nucleotide polymorphisms were identified. The expression pattern of FU was thoroughly investigated and all examined tissues express FU. It is also clear that different tissues express transcripts of different sizes and some tissues express more than one transcript. By means of nested PCR of specific regions in RT/PCR generated cDNA, it was possible to verify two alternative splicing events. This also suggests the existence of at least two additional protein isoforms besides the FU protein that has previously been described. This long FU and a much shorter isoform were compared for the ability to regulate GLI1 and GLI2. None of the FU isoforms showed any effects on GLI1 induced transcription but the long form can enhance GLI2 activity. Apparently FU did not have any effect on SUFU induced inhibition of GLI.The FU gene and its genomic structure was identified. FU is a candidate gene for SD1, but we have not identified a pathogenic mutation in the FU coding region in a family with SD1. The sequence information and expression analyses show that transcripts of different sizes are expressed and subjected to alternative splicing. Thus, mRNAs may contain different 5'UTRs and encode different protein isoforms. Furthermore, FU is able to enhance the activity of GLI2 but not of GLI1, implicating FU in some aspects of Hedgehog signaling.The  Drosophila, Hh signaling to the transcription factor Cubitus interruptus (Ci) is mediated by a protein complex consisting of Ci and three other cytosolic proteins. These are the costal 2 (cos2), suppressor of fused (su(fu)) and fused (fu), where fu is a kinase domain containing protein with positive regulatory activities in Hh induction of Ci mediated transcriptional activation. Hh binds to its receptor patched (ptc), a 12 membrane spanning protein, leading to the activation of another membrane protein smoothened (smo) . In Droed (smo) . Smo is iewed in ]. It is iewed in -7. In a iewed in . FU is aPTCH1, the human counterpart of ptc, underlie the Nevoid Basal Cell Carcinoma Syndrome (NBCCS) [SMO and SUFU mutations as well as overexpression of GLI1 or GLI2 can lead to BCC or medulloblastoma [Interestingly, it was discovered that mutations in  (NBCCS) ,10. Pati (NBCCS) ,12. Alsoblastoma -16. ThusFU gene, as well as for construction and subcloning of FU expression vectors. Using the available public databases the FU gene was found to be present in a sequenced BAC clone from chromosome 2. FU is located in the same region of chromosome 2q34-q36 to which the human limb malformation disorder Syndactyly type 1 (SD1) has recently been mapped in a large German pedigree [FU gene in an affected member from the German family [FU has been determined using an RNA array and Northern blots. FU is expressed in all 72 tested tissues. It is clear that not only a single transcript is expressed. Instead transcripts of different sizes are seen and some tissues apparently express more than one major transcript. From the genomic structure and the cDNA clones it was possible to predict several alternative splicing events and consequently the likely expression of different protein isoforms. Two of the isoforms were expressed in HEK293 cells and tested for their ability to regulate the activity of GLI1 and GLI2, showing positive effects on GLI2 but not on GLI1.Here three FU cDNA clones have been identified and used for sequence analysis, identification and structural description of the pedigree  and confpedigree . Its posn family . The tisFU gene in a 200 kb BAC clone (AC009974) from chromosome 2. The gene is localized to 2q35 at 217.56 Mb using the Ensembl [FU structure and named the gene STK36 (serine/threonine protein kinase 36). Chromosome 2q35 is the locus of several genetically based disorders. Both Syndactyly type 1 (SD1) and Brachydactyly type A1 (BDA1) have been mapped to this region [IHH (Indian Hedgehog) one of the vertebrate Hh homologues [IHH is located in the vicinity of FU on chromosome 2 (217.94 Mb) less than 400 kb away. In order to determine if alterations of FU are responsible for SD1, the FU coding region (exons 3–29) and the flanking intronic regions were sequenced using genomic DNA from an affected member of an SD1 family whose trait maps to the 2q34-q36 region [FU mutations were detected in this study, although three single nucleotide polymorphisms were identified. These included a T to C transition in intron 10, 17 bp 5' of exon 11 (IVS10-17T>C), causing gain of a BstNI site, and a G to A transition in exon 16, 17 bp 5' of the end of the exon (1748G>A), causing substitution of glutamine for arginine at amino acid 583 (R583Q) and loss of an AciI site. The altered restriction sites created by these sequence changes were tested in 44 CEPH unrelated individuals. The results showed that both changes are normal sequence variations as previously reported in the NCBI SNP database. The third change was a G to A transition in exon 27 (3008G>A), causing substitution of aspartic acid for glycine at amino acid 1003 (G1003D). By sequencing exon 27 in 8 affected and 6 unaffected members of the SD1 family [The sequence information derived from the FU cDNA clones 1HFU, 2HFU and Ngo3689 (see Methods) allowed the identification of the  Ensembl  annotatis region ,20. ReceFU exons, but they allow determination of the exon-intron organization of FU. Figure FU gene. The cDNA clones are outlined to account for the predicted structure. Only clone 1HFU and Ngo3689 contain exons from the 5'non-coding region. To the 5' side of the sequence encoded by exon 3 these clones are different, indicating that alternative 5' untranslated regions (UTR) from different exons can be used. Exons 3 to 9 encode the N-terminal kinase domain. None of the cDNA clones encodes the FU protein that has previously been described [None of the obtained cDNA clones contain sequence from all + RNA from 72 human tissues was hybridized with a labeled probe 3' of the kinase domain. It was clear from this array that all examined tissues express FU to some extent. The highest amount of FU transcripts were detected in testis and pituitary (not shown). This is in agreement with the previous results by Northern blotting, showing highest FU expression in testis [A tissue array with poly An testis . This ann testis . The Norn testis . Since on testis .To examine more specifically the expression of exons that are involved in alternative splicing events, nested PCR was performed on cDNA probes generated from whole tissue RNA by reverse transcription. Sequences containing segments including exons 8, 13 and 24 were amplified and analyzed on agarose gels .We investigated the possibility that FU expression have shown that transcripts are detected in all tissues examined. For the first time evidence is presented showing that more than one transcript can be expressed from this gene. The Northern blots clearly show that FU transcripts of different sizes indeed exist. Here the transcripts are estimated to be slightly bigger than previously reported and in some tissues more than one transcript is evident. It is clear from the available cDNAs and RT/PCR based transcript analyses that alternative splicing occurs. Additionally, it is also clear that different 5'UTRs are present in the transcripts. At least two protein isoforms, besides the previously described L-FU [Analyses of bed L-FU , may be bed L-FU . WhetherThe assessment of functionality revealed that S-FU was not able to regulate GLI1 or GLI2 when expressed in 293 cells. In contrast, both L-FU and a variant lacking a full kinase domain (2HFU) were able to enhance GLI2 induced transcription. These results are qualitatively similar to those previously reported in C3H/10T½ cells . L-FU anFU is localized on chromosome 2q35 very close to IHH. Though SD1 has been mapped to this region, we have not identified a causative role for FU in this disorder. FU consists of 29 exons of which 1 and 2 encode 5'UTRs and 3 to 9 encode a kinase domain. For the first time it is shown that transcripts of different sizes are expressed and alternative splicing takes place, probably leading to the generation of different protein isoforms. FU protein is likely to be involved in the Hedgehog signaling pathway since it can enhance the activity of GLI2. In contrast, it has no effect on GLI1 and an effect on SUFU cannot be observed in 293 cells.+. The human BAC clone AC009974 was obtained from Research Genetics . The human GLI, human SUFU, 12GLI-RE-luciferase reporter and β-galactosidase vectors have been described previously [Two almost full-length human FU clones were identified in the Incyte database. Both 1HFU and 2HFU were cloned in the vector pINCY. A third clone was available from Kazusa DNA Research Institute  and termed Ngo3689 (Gene name KIAA1278). This clone was in the vector pBluescript II SKeviously .R DNA polymerase . The cDNA for the long form of FU (L-FU) was subcloned into pCDNA3.1-HisB using the NotI and XbaI sites. 2HFU and the short FU (S-FU) cDNAs were subcloned into pCDNA3.1-HisC using the KpnI and XbaI sites.Expression constructs for different isoforms of FU was obtained by direct PCR or extension overlap PCR, using end-primers having specific restriction sites and the high fidelity VentAll PCR generated products were analyzed by DNA sequencing. The Big-Dye Terminator Cycle Sequencing kit  was used according to instructions. Sequencing was performed at CyberGene AB . Sequence alignments were done using the DIALIGN program  availablFU either as single exons with flanking intronic sequences or as products containing two exons with flanking intronic sequence and the complete intervening intron. The primer sequences can be obtained upon request. PCR was performed in a standard fashion and products were sequenced using either the Thermosequenase CyTM5.5 Dye Terminator or DYEnamic ET Dye Terminator Cycle Sequencing kits . Electrophoresis and analysis were performed on either an Automated Laser Fluorescence (ALF) DNA sequencer or MegaBACE DNA sequencer (Amersham Biosciences) after purification with Autoseq columns (Amersham Biosciences). For exon 27, the PCR product was purified using the enzymatic ExoI-SAP purification method, sequenced using the Terminator Cycle Sequencing kit (Amersham Pharmacia Biotech) and analysed on an ABI 3100 genetic analyzer (Applied Biosystems). PCR products containing exon 11 or exons 15/16 were digested with BstNI or AciI, respectively, and the bands resolved on 3–4% agarose gels to confirm sequence changes in the patient with SD1 and to determine their frequency in a panel of 44 CEPH individuals.After informed consent was obtained, blood was taken from affected and unaffected family members and DNA extracted from peripheral blood leukocytes according to standard methods. Intronic primers were designed to amplify exons 3–29 of 32P-ATP using the High Prime DNA labeling kit  according to instructions. Hybridization of Northern blots was done with labeled DNA probes in ExpressHyp (Clontech) at 68°C according to instructions. The blots were then analyzed with a Fujix Bas 2000 phosphoimager .Commercially available Human MTN 12-lane Blot 2, Human Fetal MTN Blot II and Human Endocrine System MTN Blot Northern blots  were obtained and used with PCR generated hybridization probes. DNA probes were made by direct PCR, amplifying the sequences corresponding to exon 13 and 28. The generated fragments were then labeled with The expression of exon 8, 13 and 24 sequences in mRNA was assessed by nested PCR on RT/PCR generated cDNA samples from eight different tissues as provided in Human Multi Tissue cDNA Panel II (Clontech). Two sets of primers were made for each exon to be investigated. The outer pairs were used in a first PCR using 5 μl of the cDNA and Vent polymerase. In a second PCR 0.5 μl of the first PCR products was used together with the inner primer pairs. These pairs were also used for PCR of FU cDNA clones that served as controls. The primer pairs are listed in Table The cDNA clones were used in transfections of HEK293 cells in 24 well culture plates. Basically this was done as previously described . In shorTØ contributed to the experimental design; participated in sequencing, sequence analysis and subcloning; did the gene analysis, Northern blots, nested PCR, cell experiments; and made the manuscript draft. DBE and CES designed and carried out the patient analysis; and contributed to the manuscript. MM provided clones; contributed with subcloning; made the array analysis; and contributed to the manuscript. MMN and RCB provided the SD1 patient material; performed segregation analyses in the SD1 family; and edited the manuscript. PGZ contributed to the experimental design and subcloning; and edited the manuscript. RT contributed to the experimental design; did data base analysis; and edited the manuscript.


Previous smallpox ring vaccination models based on contact tracing over a network suggest that ring vaccination would be effective, but have not explicitly included response logistics and limited numbers of vaccinators.We developed a continuous-time stochastic simulation of smallpox transmission, including network structure, post-exposure vaccination, vaccination of contacts of contacts, limited response capacity, heterogeneity in symptoms and infectiousness, vaccination prior to the discontinuation of routine vaccination, more rapid diagnosis due to public awareness, surveillance of asymptomatic contacts, and isolation of cases.We found that even in cases of very rapidly spreading smallpox, ring vaccination (when coupled with surveillance) is sufficient in most cases to eliminate smallpox quickly, assuming that 95% of household contacts are traced, 80% of workplace or social contacts are traced, and no casual contacts are traced, and that in most cases the ability to trace 1–5 individuals per day per index case is sufficient. If smallpox is assumed to be transmitted very quickly to contacts, it may at times escape containment by ring vaccination, but could be controlled in these circumstances by mass vaccination.Small introductions of smallpox are likely to be easily contained by ring vaccination, provided contact tracing is feasible. Uncertainties in the nature of bioterrorist smallpox  support continued planning for ring vaccination as well as mass vaccination. If initiated, ring vaccination should be conducted without delays in vaccination, should include contacts of contacts (whenever there is sufficient capacity) and should be accompanied by increased public awareness and surveillance. Concerns about intentional releases of smallpox have prompted extensive preparations to improve our ability to detect and respond to an outbreak of smallpox ,3,4,2. MThe Centers for Disease Control and Prevention (CDC) established ring vaccination , a straMathematical models can advance our understanding of how a smallpox outbreak might progress. Several mathematical and computer models address the question of smallpox transmission -13. The Because none of the available models includes both network structure (with explicit contact tracing) and response logistics limited by the number of available disease control investigators , we inclSmallpox was primarily a disease of close contact, especially household contacts . Such coSome evidence suggests that vaccination soon after exposure may lessen the severity of the resulting case of smallpox or possibly prevent disease entirely -20.Ring vaccination may involve not only vaccinating contacts of cases, but also contacts of contacts of cases ,22 – potLimited case-finding and vaccination capabilities lead to the possibility that it may be impossible to find newly exposed individuals and vaccinate them in time, resulting in a "race to trace" .Mild, ambulatory cases of smallpox may spread disease because such cases may be harder to recognize.Vaccination of individuals prior to the discontinuation of routine vaccination may provide some, possibly considerable, protection against infection ,23,24, aPublic awareness may lead to more rapid detection of cases.We use this model to determine what factors promote or hinder the success of ring vaccination during a smallpox outbreak, and whether ring vaccination is useful in the presence of a mass vaccination campaign. In particular, the goal of this paper is to examine the control of smallpox by contact tracing and ring vaccination using a network model which includes response logistics .focal rash, preceded in many cases by oropharyngeal lesions. In fatal cases of ordinary smallpox, death often occurred between the tenth and sixteenth day of symptoms; among survivors, most scabs had separated by day 22–27 of illness  and simulated the mean number of cases within 250 days in a population of 10000. We then computed the partial rank correlation coefficient  , as shown in Figure Because we assumed nonzero diagnosis probabilities during the prodromal period for all individuals in Figure In Figure Finally, in Figure In Figure Finally, in Figure Because our baseline hazard for infection of individuals may be larger than would be expected for naturally occurring smallpox, we examined the effect of more realistic values of this hazard. In particular, we chose different levels of ring vaccination capacity , and of the relative hazard for workplace/social contacts, and then chose values of the baseline hazard for infection varying from 0.5 per day (for a mean time to infection of 2 days) to 2 per day , and introduced 10 index cases into a population of 10000. We then repeated this 100 times, and reported the fraction of scenarios in which the number of infections ultimately exceeded 500 . These results, shown in Table Because of considerable uncertainty in the model parameters, we chose a collection of parameter values, and for each, estimated the containment probability . We estimated this containment probability by simulating the smallpox epidemic 100 times for the same parameter values, and computing the frequency out of these 100 realizations for which fewer than 500 index cases resulted within 250 days. .2), the monitored diagnosis rate φ , and the contact tracing/ring vaccination capacity per day (Kr). We then performed 100 realizations beginning with 10 index cases, and computed the containment fraction . Thus, for each of the two choices each of υ2 and φ, and for each value of Kr we examined, we obtained 1000 values of the containment fraction. We use the resulting distributions in Figure One thousand scenarios chosen from a Latin Hypercube sample were analyzed, and as indicated before, we chose the hazard for close contact transmission and the hazard for random transmission to guarantee that between 2 and 5 secondary cases per case occur, and that no more than 5% of cases are attributable to random transmission . Having chosen this collection of 1000 parameter sets, we considered two levels of two different control parameters which were applied to each (so that each of the 1000 parameter sets were simulated under four different control conditions). The first of the two control parameters was the probability of workplace/social group contact finding; we chose values of 0.8 and 0.9 for this parameter . The second of the control parameters was the rate of diagnosis  from the community of cases developing among previously identified and traced contacts who were initially asymptomatic (we refer to this as the monitored diagnosis rate); we assumed first a low level corresponding to a mean diagnosis time of one day from the onset of symptoms, and a high level corresponding to a mean time of 3 hours from the onset of symptoms (high levels of the monitored diagnosis rate correspond effectively to isolation of contacts). Finally, we assumed a doubling of the diagnosis rate after the beginning of widespread community awareness of smallpox. We then computed the containment fraction at different levels of ring vaccination capacity (contact tracing capacity per day). Thus, for each of 1000 scenarios (parameter set choices), we assigned the workplace/social group contact tracing success probability (υ-1 and 8 day-1). For low levels of ring vaccination (traceable contacts per day), the epidemic is almost never contained, but for ring vaccination levels near 50–60 per day (5–6 per index case per day), the average containment fraction became close to 1. However, this average conceals the fact that for some scenarios , control remains difficult or impossible even at high levels of ring vaccination. Therefore, in Figure In Figure fast scenario, 238 infections occurred on average and the (estimated) containment probability was 99%; for the slow scenario, on average 3587 infections occurred and the (estimated) containment probability was only 1%.Rapid contact tracing in ring vaccination may play an important role in suppressing the epidemic, since the longer it takes to trace a contact, the less likely the vaccine is to be efficacious, and the more opportunities the infected individual may have to transmit disease before they are finally located, isolated, and vaccinated if appropriate. We illustrate this possibility in Figure While Figure Public awareness of smallpox, leading to more rapid isolation and identification, may play an important role in eliminating the epidemic, as illustrated by the scenarios in Figure In many cases, however, more rapid diagnosis was not required for ring vaccination to be effective. As before, we simulated smallpox epidemics for each of 1000 calibrated scenarios, performing 100 realizations each beginning with 10 index cases, and computed the fraction of scenarios for which the epidemic was always contained (as defined earlier), assuming no change in diagnosis rates. We assumed 80 ring vaccinators per day, contact finding probabilities of 0.95 for households and 0.8 for workplace/social contacts , most individuals may already be infected when identified through contact tracing from an infective. Using the scenario we examined in Figure a = 1 hour, so that cases arising in previously contacted persons almost never transmit the infection further). We chose different levels of household and workplace/social contact finding probabilities and different levels of ring vaccination capacity, and performed 100 replications of each of the 1000 different scenarios. In Table Finally, we used the "calibrated" scenarios (parameter set choices) to explore the levels of contact finding probability needed to contain the epidemic  Table . In thesa relative infectivity during entire period is one , b the relative infectivity just prior to the rash is the same as during the first week of the rash, but during the prodromal period is 4% ; in case b (high infectivity just prior to onset of rash), loss of containment occurs 36% of the time ). Scenario a  showed loss of control in every realization. Increasing the ring vaccination capacity from 40 per day to 80 per day (results not shown) led to containment in all of the realizations with high infectivity just prior to the rash and low infectivity during the prodromal period (case b), but made no difference if the infectivity was as high during the prodromal period as during the rash (case a). While intuitively adding additional infectiousness must increase the number of secondary cases and make control more difficult, these results do illustrate that even a small amount of increased infectiousness prior to the rash (when diagnosis is more difficult) may substantially increase the difficulty of smallpox control.Transmission prior to the rash makes epidemic control more difficult. In Figure a in the figure). Specifically, we assume that severe smallpox (hemorrhagic and flat) on average takes four times longer to diagnose and isolate than ordinary smallpox (case b), that no one in the population has prior vaccination protection , that 10% more smallpox is too mild to diagnose  compared to baseline, and finally that the vaccine is completely ineffective (case e). Each of these scenarios will be discussed further below.Finally, in Figure b was motivated by the possibility that individuals with severe forms of smallpox may be more difficult to diagnose, and thus remain infectious in the community longer (despite the much greater degree of illness of such patients), or that such patients may be more infectious. In this particular case, quadrupling the mean diagnosis time led to one additional replication out of 100 in which containment was not achieved . However, we assumed that community awareness of smallpox leads to the same relative rate of increased diagnosis among severe cases as for ordinary cases, and that the most severe forms are relatively rare. In addition to the scenario shown in the figure, we also replicated the same 1000 "calibrated" simulations, assuming that in each case 40 contact tracings per day are possible and that the diagnosis time for severe cases was four times that of ordinary cases. Finally, we repeated each "calibrated" scenario 100 times assuming long diagnosis times for severe cases, and not making this assumption, and found that the difference in the decontainment fraction was not large (results not shown).Scenario c illustrates that vaccination prior to the discontinuation of routine vaccination does play a role in smallpox control by ring vaccination; there were more decontainment scenarios (5/100) when no prior protection exists in the population. The results suggest that prior vaccination aids in the control of smallpox, but that it is not strictly necessary for control . In Figure c of Figure Scenario d demonstrates that if 10% more smallpox infections . Here, with 40 contact tracings possible per day, 55% of the replications nevertheless exhibited containment even with a vaccine which offered no protection whatever. With 90 contact tracings possible per day, all replications exhibited containment even assuming no vaccine protection.Finally, scenario Although less efficient than ring vaccination in the sense that more vaccinations must be delivered to eliminate infection, comprehensive mass vaccination following the introduction of smallpox is sufficient to eliminate the infection. In Figure We constructed a simple network model of smallpox transmission, and addressed the question of what circumstances contribute to the success of a ring vaccination campaign designed to control smallpox. Our analysis focused on the use of contact tracing/ring vaccination to prevent a widespread epidemic following a deliberate release.We conducted a sensitivity analysis based on particular, but reasonable, ranges for the unknown parameters. Our results are consistent with prior vaccination models in identifying prior vaccination and ring vaccination capacity as significant factors in determining the spread of smallpox. Unsurprisingly, we also find that household size and ring vaccination speed are particularly important parameters; these results are intuitively plausible. The contact finding probability did not appear important in this analysis only because a narrow range of values was chosen.We illustrated smallpox control by presenting scenarios based on control of moderately severe smallpox epidemics. We find that swift, aggressive contact tracing and ring vaccination is is usually sufficient to bring the infection under control. Provided that there is sufficient capacity, vaccination of contacts of contacts is beneficial, and results in fewer infected individuals and more rapid elimination of infection; investigating contacts of contacts allows the chain of transmission to be outrun to some extent. When ring vaccination capacity is small, diversion of crucial resources away from contacts is harmful; contacts of contacts should only be traced and vaccinated provided that no resources are diverted away from contacts of cases. The increased surveillance (or isolation) of contacts, together with improved rates of diagnosis due to community awareness, play important roles in smallpox control; we note that in some cases, lowered diagnosis rates among severe cases contributed to a small extent to loss of epidemic control, and suggest that any public awareness campaign include information to help the public be more aware of the full spectrum of the clinical features of smallpox.One limitation of our analysis is that we chose not to explicitly incorporate the specific epidemiology of health care workers (or mortuary workers), who are likely to be exposed to infected individuals during any smallpox epidemic e.g. ,22), and, and22])While we analyzed the effect of contact tracing, case and contact isolation, and ring vaccination (together with mass vaccination), in a real smallpox epidemic, in practice, control efforts are unlikely to be limited strictly to vaccinating contacts  and isolating cases. Indeed, making vaccine available to individuals who believe they live near cases or to others on a voluntary basis occurred in smallpox control efforts in the past . VaccinaMore serious is the possibility that individuals who should be vaccinated or isolated would be missed; this could occur either because individuals or institutions did not cooperate with the disease control effort, or because the individuals simply could not be found. Our analysis suggests that ring vaccination need not be perfect to successfully contain the epidemic, and yet, under conditions where there is a high rate of infection among contacts, or a relatively high rate of casual transmission, high rates of contact finding (in excess of 90%), together with increased surveillance and contact isolation, are needed to contain the epidemic.Finally, the vaccination of individuals at low risk of contracting smallpox will cause harm due to adverse events of the vaccine; in our model, the assumed death rate due to vaccination was small compared to the probability of death from smallpox, and played essentially no role in the analysis. In practice, individuals suspected to be at high-risk for vaccine complications, but at relatively low risk for contracting smallpox, might simply be isolated or closely monitored even during an outbreak; while the presence of individuals in the population at higher risk for vaccine complications would increase the death rate during an outbreak, such individuals are unlikely to impair the containment of the epidemic .Our results support ring vaccination against epidemics of smallpox (even assuming high rates of transmission to close contacts), but do note that stochastically, for severe (rapidly transmissible) smallpox, scenarios of loss of control are seen, with resulting widespread epidemics. In scenarios in which the transmission potential of smallpox is smaller, such loss-of-control scenarios occur less frequently (results not shown). Mass vaccination campaigns, when conducted quickly and with very high coverage, do not result in loss of control in our model. Nevertheless, fewer deaths due to smallpox result when ring vaccination is conducted along with mass vaccination.Simulated smallpox epidemics with ring vaccination suggest that aggressive, fast ring vaccination can control epidemics of smallpox. To do so, however, smallpox must be identified quickly and contacts vaccinated promptly. We also identify public awareness of smallpox – leading to prompt identification of cases – as a major factor in smallpox control; in some simulations, it may play a role as significant as ring vaccination itself . Howeverwhich can facilitate more rapid identification and isolation of cases. We assumed that ring vaccination could be fast (little delay between identification of a case and vaccination of the contacts), effective , and available (there is sufficient capacity). To be effective, ring vaccination planning must yield a system capable of meeting these benchmarks; we should not only be able to assess the number of contact vaccinations that will be possible per day, but should have a plan in place to (1) identify contacts by working with individuals, employers, schools, community representatives, and authorities or businesses who may have access to information facilitating contact tracing, (2) rapidly investigate and vaccinate such individuals, perhaps using field teams managed by central dispatch. It is important to realize that for high-risk, transient, or unstably housed populations where reliable contact tracing is impossible, the conclusions of the model we present cannot be applied. It is important to note that while our model suggests that ring vaccination together with contact tracing and isolation is likely to be successful, we found that for some scenarios , epidemic containment required not only ring vaccination, but increased public awareness, the isolation of contacts, and tracing of contacts of contacts. For scenarios in which the smallpox was less transmissible, epidemic containment was possible at lower contact finding probabilities. Thus, while our simulations suggest that contact tracing/ring vaccination need not be perfect to succeed, because of uncertainties in our knowledge of the behavior of bioterrorist smallpox, it is impossible to know in advance how good it will have to be. Thus, that high contact finding rates, mass public awareness leading to early identification of cases, isolation of contacts, and investigation of contacts of contacts should all be conducted with maximum effectiveness to reduce the probability of a widespread epidemic.Because our model combines network structure with response logistics, our results support and complement the results of other investigators. Our results support the notion that prior vaccine protection may play an important role in slowing the epidemic , despiteWhile the possibility of smallpox uncontrollable by ring vaccination has made mass vaccination preparations wise, and while mass vaccination may be unavoidable in the event of a deliberate release of smallpox, we believe that ring vaccination is essential in any case. This is not only because individuals recently exposed to smallpox may be protected if they are vaccinated promptly, but because each contact identified potentially lies in the immediate future of the transmission chain. From the standpoint of epidemic control, it is far more valuable to vaccinate individuals next in the transmission chain than to vaccinate other persons. Our results support the idea that ring vaccination/case isolation may in many, if not most cases, eliminate smallpox even without mass vaccination, but also support planning for mass vaccination (so that the vastly more costly and difficult policy of mass vaccination will be available in the event of an explosive epidemic). When faced with the unknown, multiple redundant preparations are appropriate; case investigation/isolation may control smallpox even if the vaccine does not work at all, but mass vaccination is useful in the event of an explosive epidemic for which case tracking becomes impossible.None declared.TP, KH, SF, TA, RR, and DP performed the literature review , TP developed and implemented the model and simulation, TP performed the analysis of the simulation model and drafted the manuscript, DP performed analysis of contact tracing data, and KH conceived of the study. All authors contributed to, read and approved the final manuscript.The pre-publication history for this paper can be accessed here:For consistency, all references are included in the bibliography of the main text.Click here for fileFor consistency, all references are included in the bibliography of the main text.Click here for file


The physiological flux of oxygen is extreme in exercising skeletal muscle. Hypoxia is thus a critical parameter in muscle function, influencing production of ATP, utilization of energy-producing substrates, and manufacture of exhaustion-inducing metabolites. Glycolysis is the central source of anaerobic energy in animals, and this metabolic pathway is regulated under low-oxygen conditions by the transcription factor hypoxia-inducible factor 1α (HIF-1α). To determine the role of HIF-1α in regulating skeletal muscle function, we tissue-specifically deleted the gene encoding the factor in skeletal muscle. Significant exercise-induced changes in expression of genes are decreased or absent in the skeletal-muscle HIF-1α knockout mice (HIF-1α KOs); changes in activities of glycolytic enzymes are seen as well. There is an increase in activity of rate-limiting enzymes of the mitochondria in the muscles of HIF-1α KOs, indicating that the citric acid cycle and increased fatty acid oxidation may be compensating for decreased flow through the glycolytic pathway. This is corroborated by a finding of no significant decreases in muscle ATP, but significantly decreased amounts of lactate in the serum of exercising HIF-1α KOs. This metabolic shift away from glycolysis and toward oxidation has the consequence of increasing exercise times in the HIF-1α KOs. However, repeated exercise trials give rise to extensive muscle damage in HIF-1α KOs, ultimately resulting in greatly reduced exercise times relative to wild-type animals. The muscle damage seen is similar to that detected in humans in diseases caused by deficiencies in skeletal muscle glycogenolysis and glycolysis. Thus, these results demonstrate an important role for the HIF-1 pathway in the metabolic control of muscle function. Mice that can't express HIF-1α in skeletal muscle don't induce glycolytic genes and thus switch to aerobic metabolism allowing them to run uphill longer than the their wild-type littermates During exercise in normoxia, the partial pressure of oxygen in muscle tissue has been shown to dip to as low as 3.1 mm Hg, whereas in the capillary, it remains at 38 mm Hg . In ordeHIF-1α via the use of a conditionally targeted allele of the gene , the frequency of excision was evaluated through real-time PCR techniques. We saw deletion frequencies consistent with those described previously for this cre recombinase transgene . LDH activity was also increased in the WT mice, although the level did not reach statistical significance. Activities of both PK and LDH were not significantly changed in HIF-1α KO muscles following exercise. Increased activities of PK, and subsequently LDH, could be expected to lead to increased levels of lactate in the WT mice relative to HIF-1α KOs.In p = 0.10) toward an increased amount of hexose monophosphates (HMPs), which are pre-PFK glycolytic metabolites, following stimulation of the HIF-1α KO muscle. This increase was not due to differences in glucose uptake, since animals of both genotypes were able to significantly increase intramuscular glucose to a similar degree  and McArdle's disease . We analty acids . Increasty acids , althougty acids . This dep < 0.05).As mentioned above, patients with muscle glycolytic deficiencies demonstrate both increased exercise-induced muscle damage and a “second wind”; the latter phenomenon allows them to exercise for extended periods of time at submaximal levels. This is thought to be due to an increase in rates of oxidative ATP production, and a decreased utilization of and need for muscle glycogen . To assep < 0.01, Further testing was done to determine the parameters of this increased endurance. HIF-1α KOs were run on an enclosed treadmill, with a 5° incline and an initial velocity of 10 m/min, with an increase in velocity every 5 min. In their first runs, HIF-1α KOs again had significantly greater endurance, as shown by their consistently longer run times compared to WT controls ; HIF-1α KOs did the reverse, and ran for significantly shorter times downhill than uphill (p < 0.05). Substrate utilization confirms the shift toward glycolytic fibers in downhill running; both genotypes had higher average respiratory exchange ratio (RER) values when running downhill compared with running uphill  than to concentric exercise  , mice frg uphill D and 6E.p < 0.01, p < 0.05). Histological examination of gastrocnemius tissue following 1 d of recovery revealed significantly greater amounts of muscle damage in HIF-1α KO tissue than WT tissue , indicative of skeletal muscle damage. To further investigate this finding, mice were run on a treadmill daily for 4 d. By the second day, the trend for increased endurance in the HIF-1α KOs was absent, and by the final day, HIF-1α KOs were running for significantly shorter times than they had on the first day  and the ABI Prism 7700 Sequence Detector (Applied Biosystems). Conditions for the PCR were one 10-min incubation at 95 °C (polymerase activation), followed by 40 cycles of 15 s at 95 °C (denaturation) and 1 min at 60 °C . The degree of excision was calculated by comparing HIF-1α DNA levels to c-Jun DNA levels. HIF-1α real-time PCR primers and probe were as follows: forward primer, HIFLOX501/F 5′-CTATGGAGGCCAGAAGAGGGTAT-3′; reverse primer, HIFLOX574/R 5′-CCCACATCAGGTGGCTCATAA-3′; probe, HIFLOX/P 5′-(6FAM)AGATCCCTTGAAGCTAG(MGBNFQ)-3′.Mice from the above crosses were genotyped using DNA extracted from tail sections. DNA was then extracted from the gastrocnemius, heart, liver, and uterus of eight 4-mo–old, Paraffined gastrocnemius sections were deparaffinized and stained with Gill II hematoxylin. Sections were then washed successively in water, a bluing agent, water again, and 95% ethanol, and restained with eosin. Hematoxylin and eosin staining was performed by the University of California at San Diego (UCSD) Cancer Center Histology Resource . Imaging was performed on sections mounted on slides using Cytoseal 60 . Electron microscopy was performed by standard methods on gastrocnemius muscle. Briefly, fixation was by 25.5% glutaraldehyde in 0.1 M sodium cacodylate buffer (pH 7.4). Postfix was in 1% osmium tetroxide. The section was stained in 2% uranyl acetate in sodium maleate buffer (pH 5.2), then placed in Epon resin , and cured overnight at 60 °C. Fiber typing was performed using the metachromatic dye ATPase method . PAS stan = 10; KO, n = 14) were run either on an Omnipacer treadmill  or on an enclosed-chamber modular treadmill (Columbus Instruments) with a 5° incline at an initial velocity of 10 m/min. Velocity was increased by 2 m/min every 5 min during the assessment. Exhaustion was determined to be the point at which the animal would not resume running when provoked through a low-voltage power grid. Gas flow (O2 and CO2) into and out of the enclosed chamber treadmill was monitored using the Paramax O2 sensor and a CO2 sensor (Columbus Instruments) and analyzed using Oxymax software (Columbus Instruments) to determine metabolic parameters. The downhill running assessment  was carried out in the enclosed-chamber modular treadmill at a 10° decline using the same protocol as above.Untrained, age-matched WT mice and HIF-1α KOs  was placed in a 30 °C water bath with mild turbulence. Exhaustion was determined to be the point at which the animal experienced three successive periods below the surface of more than 3 s.In the swimming exhaustion assessment, a second group of WT and HIF-1α KOs  and attached to a force transducer to record contractile force. Muscles were electrically stimulated through excitation of the sciatic nerve. Stimulation was in the form of 8–10-V direct titanic contractions using 200-ms trains at 70 Hz with 0.2 ms duration. Initial frequency of tetanic contraction was one every 8 s and was increased every 2 minutes to one every 4 s and one every 3 s, up to the end point of 6 min. Isolated muscles were then immediately harvested and snap-frozen for ATP, lactate, phosphocreatine, and glycogen analyses. Samples were freeze-dried and analyzed by enzymatic assay as has been previously described . Reverse transcription was performed using the Superscript First Stand Synthesis System for RT-PCR . Amplification was performed using the ABIPrism 7700 as described above. Reverse transcription real-time PCR primers and probes were as follows. For PGK-1: reverse primer, PGK/R 5′-CAGGACCATTCCAAACAATCTG-3′; forward primer, PGK/F 5′-CTGTGGTACTGAGAGCAGCAAGA-3′; probe, PGK/P 5′-(6∼FAM)TAGCTCGACCCA-CAGCCTCGGCATAT(TAMRA)-(phosphate)-3′. For VEGF-A: reverse primer, VEGF/R 5′-ATCCGCATGATCTGCATGG-3′; forward primer, VEGF/F 5′-AGTCCCATGAAGTGATCAAGTTCA-3; probe, VEGF/P (6∼FAM)TGCCCACGTCAGAGAGCAACATCAC(BHQ∼6∼FAM). For GLUT4: reverse primer, GLUT-4/R 5′-CCCATGCCGACAATGAAGTT-3′; forward primer, GLUT-4/F 5′-TGTGGCCTTCTTTGAGATTGG-3′; probe, GLUT-4/P 5′(6-FAM)TGGCCCCATTCCCTGGTTCATT(BHQ1-Q)-3′. For PFK-M: reverse primer, PFK-M/R 5′-AAGTCGTGCAGATGGTGTTCAG-3′; forward primer, PFK-M/F 5′-GCCACGGTTTCCAATAACGT-3′; probe, PFK-M/P 5′-(6-FAM)CCTGGGTCAGACTTCAGCATCGGG(BHQ1-Q)-3′. For LDH-A: reverse primer, LDH-A/R 5′-ATGCACCCGCCTAAGGTTCTT-3′; forward primer, LDH-A/F 5′-TGCCTACGAGGTGATCAAGCT-3′; probe, LDH-A/P 5′-(6- FAM)TGGCAGACTTGGCTGAGAGCAT(BHQ1-Q)-3′.n = 5; KO, n = 6) were run on a treadmill at 25 m/min for 30 min. Following the run, mice were euthanized and RNA was isolated and analyzed as described above.For changes in gene expression due to exercise, age-matched male mice  were run on a treadmill using the same protocol as for the gene expression analysis. Tissue was harvested after the run and from resting mice , and enzymes were extracted and analyzed spectrophotometrically as has been described  by the UCSD Animal Care Program Diagnostic Laboratory.Creatine kinase levels were analyzed from serum from WT mice and HIF-1α KOs 24 h after running-induced exhaustion using a kit from Sigma . Creatine kinase isoforms were analyzed enzymatically and then fractionated by gel electrophoresis. Serum lactate levels were analyzed by the UCSD Comparative Neuromuscular Laboratory from blood obtained by cardiac puncture from six WT mice and six HIF-1α KOs following 25 min running time on the treadmill ramp at 25 m/min. Hematocrit and hemoglobin levels were measured from resting mice  or glucose tolerance group . Experimental animals were injected with 0.3 g/ml glucose in PBS to achieve a dosage of 2 g/kg. Sham animals were injected with an equivalent amount of PBS. Blood was drawn from the tail at time intervals of 0, 15, 30, 60, and 120 min. Samples were then centrifuged to isolate plasma. Plasma blood glucose was quantified using the Infinity Glucose Kit (Sigma).Animals were assigned into either a sham  were mechanically dissected from the flexor brevis muscle and loaded with fura-2. Fibers were then stimulated while force generation and Ca2+ release were monitored.Intact individual muscle fibers  on the Omnipacer Treadmill or the enclosed-chamber modular treadmill using the same exhaustion protocol described above. Mice ran according to this protocol every day for 4 d with a minimum of 22 h of rest between trials. Following the fourth trial, mice were given 24 h of rest and then euthanized. Tissue was harvested and stained using hematoxylin-eosin (as described above) and α-PCNA  combined with a DAB Kit .Endurance was tested by running 24 animals  were carried out using StatView software  or Prism software .


Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normalization techniques is the locally weighted scatterplot smoothing (LOWESS) algorithm. However, a much overlooked concern with the LOWESS normalization strategy deals with choosing the appropriate parameters. Parameters are usually chosen arbitrarily, which may reduce the efficiency of the normalization and result in non-optimally normalized data. Thus, there is a need to explore LOWESS parameter selection in greater detail.In this work, we discuss how to choose parameters for the LOWESS method. Moreover, we present an optimization approach for obtaining the fraction of data points utilized in the local regression and analyze results for local print-tip normalization. The optimization procedure determines the bandwidth parameter for the local regression by minimizing a cost function that represents the mean-squared difference between the LOWESS estimates and the normalization reference level. We demonstrate the utility of the systematic parameter selection using two publicly available data sets. The first data set consists of three self versus self hybridizations, which allow for a quantitative study of the optimization method. The second data set contains a collection of DNA microarray data from a breast cancer study utilizing four breast cancer cell lines. Our results show that different parameter choices for the bandwidth window yield dramatically different calibration results in both studies.Results derived from the self versus self experiment indicate that the proposed optimization approach is a plausible solution for estimating the LOWESS parameters, while results from the breast cancer experiment show that the optimization procedure is readily applicable to real-life microarray data normalization. In summary, the systematic approach to obtain critical parameters in the LOWESS technique is likely to produce data that optimally meets assumptions made in the data preprocessing step and thereby makes studies utilizing the LOWESS method unambiguous and easier to repeat. DNA microarray technology has become a standard tool in biomedical research for large-scale transcriptional monitoring . A growif of neighboring samples to be included in the weighted polynomial fit is particularly sensitive and its variation greatly affects the normalization results. This parameter should be carefully chosen through a systematic procedure where experimental assumptions are clearly specified. Benefits in the normalization process may be considered to be small in their own right, but these improvements are extremely meaningful in the context of searching for subtle biological differences in gene expression.Microarray data preprocessing contains three phases: quality control, within-slide normalization, and between-slide normalization. Within-slide normalization aims to correct dye incorporation differences which affects all the genes similarly, or genes with the same intensity similarly . One scaf in print-tip LOWESS normalization. Results are compared to common, arbitrary selections of f. The proposed procedure first examines a case study where we have utilized three quality filtered, self versus self hybridization experiments. With self versus self experiments, we are able to clearly detect normalization differences. Such analysis also verifies that the optimized method produces properly calibrated ratios. Our proposed technique is also demonstrated on a typical set of quality filtered microarray data. We utilize a set of breast cancer data that has replicated measurements for four different tumor cell lines [f. Our self versus self data, including the original TIFF images, are available online [We outline an optimization-based procedure for obtaining a systematic value for ll lines . In addie online  and the e online . denote the background corrected selection for the intensity of the jth gene of the Cy3 (green) colored sample. Similarly, let  denote the jth gene of the Cy5 (red) colored sample. One key issue for the dyes is that they are consistently imbalanced [Within-slide normalization is used to correct the dye intensity errors introduced across one microarray slide. The result of this step provides the normalized, calibrated ratios. Let balanced ,13. Diffbalanced ,24. Dye n total gene expression ratios and we denote the observed vector of ratios for a single experiment as r ∈ ℝn × 1. The calibrated ratio of expression for each gene is obtained by dividing the test by the reference sample intensities with the proper normalization factor in the denominator,For a single microarray experiment, there are i = 1, 2..., n, where n is the total number of spots on a microarray. The normalization factor, denoted by Φ(·), is a function of data-dependent variables. If the dyes are linearly dependent, it can be assumed that the normalization function is a constant, namely Φ(·) = φ. Many studies have looked at linear dependencies [for ndencies , as wellMany studies perform within-slide normalization in a global manner by assuming the error effects are stationary across an entire slide. This is currently true for the cases of Affymetrix GeneChip or Agilent oligonucleotide microarrays. For cDNA microarrays, however, the sources of variation typically originate in a localized or spatial manner , mainly et al. [Ig, Ir)-scatterplot in log2-space for determining the value of Φ(·). It has been suggested in separate works by Dudoit et al. [et al. [2-based scatterplot of the average fluorescence intensity A versus the transformed ratio M should be used instead of a simple, log2-based intensity scatterplot. This type of scatterplot is commonly known as a Bland-Altman plot in the statistics literature. The values for A and M are given as,One of the most widely used nonlinear correction techniques is the LOWESS method, which was first applied to microarray data by Yang et al. . The maiet al. . Subsequt et al.  and Yang [et al.  that a li = 1, 2,..., n. Equations (2) and (3) are preferred over the original intensities because the -scatterplot may reveal artifacts that are not clearly visible in the ordinary intensity scatterplot. Such a transformation represents a scaled, 45° rotation of the -coordinate system [for e system .Mj = g(Aj) + εj, where the jth transformed ratio Mj is a function of the corresponding overall intensity Aj and a zero mean random variable εj. The smoothed point at Aj using LOWESS with a degree d polynomial is , where  is the fitted value of the regression. The LOWESS estimate, , is a weighted linear combination of the MiThe smoothing procedure has been designed to accommodate measured scatterplot data obeying the form hi(Aj) depend on Ai, ∀i, but not on the Mi. The LOWESS algorithm contains four data-specific parameters, namely the polynomial order d, the number of LOWESS algorithmic iterations t, the weight function w(·), and the fraction of the data points used in the local regression f. Consequently, these parameters all affect the values of the weights hi(Aj) in Eq. (4). For a complete outline of the LOWESS algorithm, consult [d = 0, 1, or 2, depending on the choice of - or -coordinate systems, the tri-cube weight function is quite standardized for all types of data [t = 3. The final parameter must be chosen where f ∈ . The value of each ψk,i(·) is a function of experiment-specific parameters such as temperature or other environment settings which may differ from sample to sample in a single experiment. Accordingly, the cost function to be minimized for the kth print-tip group across all transformed ratios isFor a microarray experiment, there are a total of ℓ print-tips used on a single slide. In order to reliably determine the value of fk ∈  is unknown, reliable estimates that reflect experiment-specific assumptions may be used. Usually there are tens of thousands of genes in a microarray study and a plausible assumption is that the mean of the log2-transformed ratios after normalization is zero. Also, in a variety of experiments, platform-dependent control transcripts that are known to have certain expression at a constant level may be utilized in the optimized approach. Furthermore, in our breast cancer case study we show how to obtain statistically reliable estimates of ψk,i(·) from replicate slides. We also show how our approach may be used if replicates are not available for typical microarray studies. Ultimately, the optimized approach requires experimenters to explicitly state their assumptions behind the study, which is systematically better than arbitrarily choosing parameter values. In addition, determining an experiment-specific fk by trial and error may be time consuming and will oftentimes lead to non-optimal results. The chosen optimization algorithm for minimizing the corresponding cost function is based on a combination of golden-section search and successive parabolic interpolation as outlined by Forsythe et al. [fk for minimizing δk(fk) for each print-tip, k = 1,..., ℓ within a tolerance of ±0.01. Each print-tip, resultingly, may have a different, optimal bandwidth parameter.with the constraint that e et al. . This ap have been obtained, calibrating the intensities for all the Ak,i is given asAfter the estimates i = 1,..., nk, and k = 1,..., ℓ. For the local LOWESS normalization within each print-tip group, the issue of how the total intensities are spread about the sample mean for the group becomes a factor to consider when normalizing the data [2-ratios from the different print-tip groups are usually centered around zero. Some print-tips may have larger variances compared to others and an appropriate scale adjustment is needed to account for such differences. One proposed approach is to find the maximum likelihood estimate for the scale of the variance for each print-tip group [2-ratios from the kth print-tip group follow a normal distribution with mean zero and variance σ2, where σ2 is the variance of the true log2-ratios and  is the estimated scale factor for the kth print-tip group. However, this is only valid for certain types of data that reasonably follow a normal distribution and in our work we observe that this assumption may often times lead to undesirable results. Refer to [for the data . After nip group . This meRefer to  for furtAnother approach proposed here that is able to deal with the variance scaling issue is to introduce a weighting factor in the calibration function that is of the formi = 1,..., nk, k = 1,..., ℓ, and where the weight is given as . The bias-corrected sample variance for the kth print-tip is denoted by  and is given asfor  denotes the sample mean for print-tip k. Furthermore, the minimum sample variance is given aswhere λk takes values over , we have obtained nearly identical sample means, but less total variance for the resulting data compared to previously published techniques. The computation of λk is straightforward and easy to calculate but our novel variance stabilization procedure does not take into account any heteroscedasticity in the data, namely observed increasing ratio variance with decreasing measurement intensity A. A rigorous comparison of print-tip scaling is beyond the scope of this contribution, but it is noted that the different scaling procedures affect the overall calibration scheme.Compared to the maximum likelihood method outlined by , this meet al. [et al. [et al. [fk was performed and print-tip LOWESS normalization results are compared to the results using arbitrary choices of the parameter fk. The implementation took a few minutes to run on a standard desktop PC running MATLAB.To demonstrate the utility of our optimized LOWESS normalization procedure, we first utilized a set of three self versus self experiments , BT-474,et al. . For eac [et al.  and the  [et al. . Optimiz2 - log2 space should be distributed along a straight line that intersects zero with a slope of unity. In the -coordinate system, all values of M should lie on a straight line at M = 0 for all values of A; this means that the calibrated ratios should ideally be unity for all variables. Correspondingly, the cost measure is given when ψk,i(·) = 0, , in Eq. (5) for the -coordinate systems. Separate trials were conducted using weighted, zeroth-order (d = 0), first-order (d = 1), and quadratic (d = 2) polynomial fits. For all trials, the number of print-tip LOWESS iterations was fixed at t = 3. The weight function used is given by Cleveland [fk. As a comparison to arbitrary selections of fk, the print-tip normalization was also carried out using fk = 0.2, 0.4, 0.6, and 0.8 in separate trials. Figure M(Arb), M(Opt))-scatterplot comparison between the calibration results with d = 1 using optimal fk and arbitrary fk for the BT-474 self versus self experiment. The points that deviate from the blue line are the genes that are most affected by the choice of fk. The MArb)  surely will not be equal to zero for all genes. Accordingly, implementing the cost function in Eq. (5) becomes an immediate challenge since the normalization reference level of all the genes for a typical microarray experiment may be diffcult to determine with complete accuracy. We note that our cost function still may be used with the assumption that the sample mean for each print tip before log2-transformation is unity. In most microarray experiments, many genes may be assumed to have constant RNA concentrations while smaller numbers of genes may be over or under expressed, namely their sample mean over all the genes is zero, . Using this assumption in Eq. (5), our experiments show that by minimizing the cost function in this context, like in the self versus self case study, we are able to systematically choose fk and the only consequence is that the minimum of the cost will not be as low as in the self versus self scenario where all genes should be constantly expressed. The main benefit of utilizing LOWESS for microarray normalization is that it is robust to extreme outliers and the cost function implemented in this fashion further restricts the effects of such extreme points in the regression. Ultimately, this implementation results in reliably calibrated ratios compared to the arbitrary formulation where different choices of fk affect the resulting data.One immediate concern for typical experimental microarray data is that many genes may be over- or under-expressed and the true, transformed gene expression ratio fk. After an initial round of optimized LOWESS normalization for each replicate slide with ψk,i(·) = 0 in Eq. (5), the sample mean for each gene may then be calculated using the replicates. The normalization reference levels ψk,i(·) were reassigned these average gene expression values in Eq. (5). Each experiment was then separately calibrated a second and final time using the optimization approach and the final results were noticeably different compared to the normalized data using f = 0.2 that Järvinen et al. posted on their website [M = 0 in the -scatterplot if the cost function approach is used. Consequently, the calibrated data reach a stable domain with a small dynamic range. Empirically, we found that performing optimized normalization in an iterative manner will not propagate regression effects through to disrupt the underlying structure of the data.Since a single microarray experiment represents an observation, multiple observations would be needed to compute a reliable estimate of the true transformed ratio values. The use of only a small number of replicate slides may be satisfactorily used to determine reliable estimates of true gene expression and one study showed that three replicates suffce for significantly reducing experimental variability . With th website . A notewfk for the first replicate BT-474 hybridization. Some genes in this plot report 4-fold differences and ultimately these differences affect data analysis. Consequently, the errant choice of this parameter fk may have deleterious effects on different biological studies. To illustrate the differences for one representative print-tip in this breast cancer study for the first replicate of the BT-474 cell line, Figure k = 16 are highlighted in black. In this plot, we show that the regression obtained by the optimized choice of f16 differs from the one obtained by arbitrarily selecting f16 = 0.2 and the calibration results are thus affected. Figure fk.Figure kth print-tip groupAs further illustration of the calibration differences between the optimized and arbitrary calibration results, we employ a goodness-of-fit test . We wishM(Arb) and M(Opt) are the arbitrary and optimized calibration results, and the denominator within the summation is simply the variance of the difference between M(Arb) and M(Opt). The null hypothesis is defined to be H0: the normalized ratios using arbitrary f are comparable to ones using optimized f. We tested against p < 0.05 for the  distribution and reported the alternative hypothesis for a few print-tip groups on almost all the slides. In this analysis, we compared optimized choices of f for each print-tip to the arbitrary choices f = 0.2, 0.4, 0.6, and 0.8. By looking across each replicate of the calibrated data for all four breast cancer cell lines, almost all slides in this study reported at least one print-tip to have statistically different calibration results based on the choice of fk. Often times a single slide would report two or three print-tip groups that had statistically different calibration results.where et al. [homeo box B7, which was validated with RT-PCR [v-erb-b2, which is known to be over-expressed in the BT-474 cell line [et al. [homeo box B7 gene shows that it falls within the top 18% of overall gene expression, but by using the optimized approach we report it to be within the top 13%. For the v-erb-b2 gene, both calibration techniques report that this gene falls within the top 1% of the genes in terms of expression. As a result, for the homeo box B7 gene, the calibration factor fk is responsible for about 5% change in the reported gene expression. This is a dramatic result that may influence how the expression for this gene may be interpreted in comparison to the accepted biological knowledge of a certain experiment. As public data from microarray experiments continues to become available, the knowledge of certain genes will undoubtedly be uncovered for well-studied cell lines and this information will help further assess normalization and microarray quality control tasks.In addition to statistical analysis, genes that exhibit known over-expression in the BT-474 cell line data  were selet al. , our reset al. . Two genh RT-PCR , and v-eell line . The res [et al.  for caliet al. [f was chosen arbitrarily and its value was not reported in the study. Consequently, reproduction and verification of these results may be diffcult. For instance, some of the important biological findings, such as start and end points of amplifications and deletions, may be adversely affected by different choices of f.The LOWESS method has recently been applied in other applications for the biological sciences. Comparative genomic hybridization (CGH) is a molecular cytogenetic method of screening a tumor for genetic changes. The alterations are classified as DNA gains and losses and they reveal a characteristic pattern that includes mutations at chromosomal and subchromosomal levels. Our proposed optimized scheme is directly applicable to the application of calibrating CGH microarray experiments, as well as for data analysis aspects. For example, the work of Clark et al.  utilizedet al. [f result in noticeably different correction effects and the optimization method proposed here may be suitable for enhancing such a study. Adaptations to the cost function may be utilized to handle this type of data. In addition, analysis of other types of scatterplot data by utilizing the LOWESS method with an arbitrary choice for the bandwidth parameter is undoubtedly susceptible to varied interpretations or errant conclusions [In addition to CGH analysis, LOWESS has found application in case-control studies where logistic regression has been used to model the relationship between binary responses and continuous predictor variables . In theset al.  clearly clusions ,39.d in the weighted polynomial fit. A higher-order (d > 2), weighted polynomial is rarely needed based on the argument that such an assumption is, to a certain extent, over-fitting the data. From the findings of our study, we find that it is better to use a linear estimate based on minimizing the estimate errors across -scatterplots. Consequently, different choices of d resulted in different optimized values for f. The reason is that for the higher-order polynomial, it is beneficial in general to retain a larger fraction of the values of A for the weight function in computing the polynomial coeffcients. It is very important to carefully select f since ultimately, the bandwidth is a function of the polynomial order.Another result of this optimized calibration study is that we uncovered a better understanding of choosing the parameter f . For one, print-tips are physically different and they are considered to have different types of errors introduced based on these properties. In the formulation of normalization, it is imperative to address such subtle issues when choosing and implementing any algorithm.Here, we also reaffirmed the idea that the quality filtering of ratios and spots is a necessary step that should precede all experimental microarray data handling procedures, whether it is scatterplot-based normalization or any other normalization method, since errant ratios would surely have a deleterious affect on the calibration. For instance, in the BT-474 data, the first replicate slide had poor ratio quality for a handful of genes. Calibration without considering or removing these errant spots resulted in less reliable results. This study addresses the issue of locating sources of experimental error for print-tips that have high sensitivity for the parameter f for the LOWESS algorithm results in noticeably different normalization results. This proposed method requires the calibration step to clearly state the assumptions used for within-slide normalization. Our optimization algorithm is more systematic than simply choosing an arbitrary parameter value or through trial and error techniques since the optimized approach relies on the actual underlying structure of the data. We also stress that such an optimization algorithm may also be utilized for other studies in addition to DNA microarray normalization treatments. Proper changes need to be made to Eq. (5) to reflect the ideal model for the data captured in the function ψk,i(·), but in some studies, such a function may be satisfactorily determined or estimated from the data.The systematic choice of the parameters in the LOWESS algorithm has not been previously addressed in the microarray literature and the method proposed here may be utilized in different microarray platforms. Such a treatment is also important for a wide variety of applications that employ scatterplot-based regression. The findings of this study illustrate that by choosing different values of et al. [et al. [et al. [et al. [et al. [For the self versus self hybridizations, custom cDNA microarray experiments proceed as follows. Altogether, three microarray hybridizations were performed using custom printed cDNA microarray slides from the same print batch. Labelling, hybridization and washing were done as described previously by Monni et al.  and Järv [et al. . Briefly [et al. . Microar [et al. . For the [et al.  and deta [et al. .et al. [et al. [All microarray experiments contained in this work were conducted and spotted using groups of ℓ = 32 print-tips, with each tip being responsible for either 384 or 420 spots in their respective subarray. In order to reduce the effects of spots whose intensities are not reliable due to experimental or printing errors, we used two separate quality filtering methods and normalized the intensities after discarding values that were detected unreliable. The assessment of ratio quality was performed using the method proposed by Chen et al.  and rati [et al. . In this [et al. . The traJAB developed the mathematical formulation of the problem, implemented the optimized normalization algorithm in MATLAB, developed the statistical analysis, and wrote the manuscript. SH developed the LOWESS normalization software in MATLAB, coordinated spot quality filtering, and assisted in drafting the manuscript. AKJ conducted the self versus self microarray experiments and performed ratio quality filtering for data analysis. HE assisted in data preparation and in drafting the manuscript. SKM participated in the design and coordination of the study and assisted in drafting the manuscript. JA reviewed the statistical analysis and participated in the design and coordination of the study. All authors read and approved the final manuscript.


Although serotonin reuptake inhibitors are effective in the treatment of OCD, many patients fail to respond to these agents. Growing evidence from open-label and placebo-controlled trials suggests a role for augmentation of SRIs with atypical antipsychotics in OCD. Quetiapine is generally well tolerated and previous open-label data has produced mixed results in OCD and additional controlled data is needed.We undertook a double-blind, randomised, parallel-group, flexible-dose, placebo-controlled study of quetiapine augmentation in subjects who had responded inadequately to open-label treatment with an SRI for 12 weeks. Following informed consent and screening, forty-two subjects were randomised to either placebo or quetiapine for six weeks.There was significant improvement from baseline to endpoint on the Yale-Brown Obsessive-Compulsive Scale in both the quetiapine and placebo groups  with 40% (n = 8) of quetiapine and 47.6% (n = 10) of placebo treated subjects being classified as responders. Quetiapine did not demonstrate a significant benefit over placebo at the end of the six-week treatment period (p = .636). Similarly quetiapine failed to separate from placebo in the subgroup of subjects (n = 10) with co-morbid tics. Quetiapine was generally well tolerated.In this study, quetiapine augmentation was no more effective than placebo augmentation of SRIs. A number of limitations in study design make comparisons with previous studies in this area difficult and probably contributed to our negative findings. Future work in this important clinical area should address these limitations. Obsessive-compulsive disorder (OCD) is a prevalent, chronic and disabling disorder . ControlFrom this it is clear that a need exists to pursue more effective treatments for those with OCD who fail to respond or respond inadequately to SRI's. To this end, preliminary evidence supports a role for the addition of atypical antipsychotics to SRIs in OCD. These agents combine serotonin-dopamine antagonism with the advantage of being well tolerated including a low potential for inducing motor side-effects.To date a number of open-label studies have suggested that augmenting SRI's with atypical antipsychotics is an effective strategy for treatment-refractory OCD. These include support for risperidone -7, olanzThe outcome of the first controlled study in this area with the antipsychotic haloperidol demonstrated preferential benefit for refractory OCD subjects with co-morbid tic disorder . In two Despite some mixed evidence in this area, in general the available literature appears to support the use of relatively short trials with low doses of antipsychotic agents as augmentation to SRIs. Quetiapine has a particularly interesting profile in that it is the only available antipsychotic with significant 5-HT1D effects and this serotonin receptor subtype has been implicated in OCD ,27.Our objective was to examine the effects of quetiapine augmentation in subjects with OCD who had failed to respond adequately to a 12 week trial of an SRI, employing a double-blind, placebo-controlled, six week study design.Forty two subjects aged 18–65 years inclusive were recruited in our multi-centre study comprising five sites in South Africa and one in Canada. Recruitment took place between May 2002 and November 2003. Prior to commencement, all sites in the study received approval from their relevant Research Ethics committees/Institutional review boards and regulatory authorities. All subjects provided written informed consent prior to the commencement of any study-related procedures. Diagnosis was confirmed using the MINI Neuropsychiatric Interview   to ensurAll subjects were treated and monitored by investigators for the minimum twelve week duration of SRI-alone treatment phase before inclusion into this study. This was to ensure that patients met criteria for duration of SRI treatment which included at least 6 weeks on the maximum tolerated dose of the relevant SRI. Sample size calculations were based conservatively on similar work in this area ,21. AccoA double-blind, randomised, parallel-group six-week augmentation with quetiapine or matching placebo of the SRI to which participants had not responded adequately, was undertaken. Specific SRI's, mean doses and dose range are provided in Table At baseline participants were randomly allocated to receive treatment with either quetiapine or placebo using a computer generated schedule and numbered dispensing wallets. A flexible dosing schedule was initiated at 25 mg per day for one week and then doubled weekly to the start of week 4. Based on Clinical Global Impression of Improvement (CGI-I) scores of minimally improved or worse, clinicians were permitted to increase the dose to a maximum of 300 mg per day for the final two weeks of the study. In addition to clinical measures of improvement, clinicians also considered patient tolerability in their decision to adjust doses. Following completion of the treatment phase, subjects were withdrawn from study medication while continuing their SRIs. All subjects were then followed up for any adverse effects.Patients were assessed by clinicians at baseline and on completion of weeks 2, 4 and 6. Telephonic assessments were performed on completion of weeks 1 and 3. Symptoms of obsessive-compulsive disorder were measured by the same clinician where possible at all study visits using the Yale Brown Obsessive Compulsive Scale YBOCS) ,31. A glOur primary outcome measures for OCD symptoms were (1) the change in YBOCS score from baseline to endpoint and (2) the clinical global impression of improvement (CGI-I) at endpoint. In the final analysis, treatment response was defined as a 25% or greater reduction in YBOCS score and a CGI-I of 1 (very much improved) or 2 (much improved) from baseline to endpoint. Secondary outcome measures included the MADRS, SDS and YGTSS (in subjects with co-morbid tics).Thirty-nine of the forty-two randomised subjects successfully completed the six-week treatment phase. Two subjects withdrew from the study prematurely (Week 1 and Week 4) due to severe levels of sedation. In both of these cases at least one week of study medication had been taken and at least one post-baseline clinical assessment was completed. Both of these subjects were included in the final analysis using data from the last observation carried forward (LOCF). The single subject not included in the efficacy analysis completed the study, but was found not to have correctly fulfilled the study definition of treatment refractoriness and was excluded. Twenty subjects were allocated to the quetiapine arm and twenty-one to the placebo arm. Student's t-tests were used to determine any baseline differences in the groups for age, gender, number of previous trials of SSRI's, severity of symptoms in relation to OCD, depressive symptoms, and CGI-S. Analysis of variance was undertaken with group and tics as factors. All tests were two-tailed with p-values of less than 0.05 considered significant.For the final analysis, our sample comprised 19 men and 22 women. Baseline characteristics of two treatment groups did not differ with respect to age (years) (quetiapine group 33.8(SD 9.66), placebo group 31.81 (SD 12.14); p = 0.57), gender (p = 0.29), number of previous adequate SRI trials (quetiapine 1.55 (SD 1), placebo 1.62 (SD 1.02) (p = 0.83), baseline severity of OCD , depressive symptoms (p = 0.91), patient-rated disability (p = 0.28) or the presence  of co-morbid tics.For the primary outcome measure of severity (YBOCS), quetiapine p < 0.0001) and placebo (p = 0.001) augmentation of an SRI significantly improved symptoms of OCD. However quetiapine did not demonstrate significant benefit over placebo at the end of the six-week treatment period  ; placebo n = 1(20%)) were classified as YBOCS responders. The reduction in the YGTSS did not differ significantly between treatment groups with tics .Severity ratings for depressive symptoms (MADRS) were low at baseline , showed little change over the study period, and at week 6 remained similar for both groups .The mean daily dose at week 6 for the quetiapine group was 168.75 mg (SD 120.82) compared to 228.57 mg (SD 99.46) per day for those on placebo. Quetiapine responders  did not differ significantly from quetiapine non-responders  in their mean daily dose at Week 6 (p = .585). Furthermore, within the quetiapine group, participants receiving ≥ 200 mg/day  and a marginally lower percentage reduction in YBOCS at endpoint  compared to those receiving a dose ≤ 200 mg/day  at endpoint.Quetiapine was generally well tolerated and no serious adverse events (SAE's) were reported through the course of the study period. Two patients on quetiapine withdrew from the study due to severe sedation (Week 1 and Week 4) that was judged to be drug related. Otherwise adverse events were in the mild to moderate range and were mostly self-limiting. No subjects on placebo withdrew from the study. Table Our findings indicate that both quetiapine and placebo significantly reduced symptoms in subjects with OCD who had failed to respond adequately to 12 weeks of an SSRI and, that the difference between groups was not significant. Similarly in the subgroup with co-morbid tics, no preferential benefit was noted for quetiapine. Interestingly, the high placebo response was similar to that seen in a recent failed controlled trial of olanzapine , but staFirst, the duration of a therapeutic trial of an SRI prior to augmentation with an antipsychotic should be of adequate dose and duration. In our study the majority of participants had failed only the single trial of an SRI on which they continued during the study (63.4% mean 1.59). Notably only six weeks of this treatment was required at the maximum tolerated dose. Despite the notion that an optimum trial of pharmacotherapy in OCD is 12 weeks, it may be argued that higher and ultimately effective doses of an SRI had not been maintained for an optimum duration prior to randomization. Given that therapeutic doses of SRIs in OCD are usually on the upper end of the dose range, it seems feasible that the high placebo response rate may reflect a response to SRI's once they had been administered at these higher doses for the additional six weeks of the study. It seems possible that the recent study by Shapira et al  may haveIn a second and related point; the number of previous SRI trials in the subgroup receiving quetiapine did not predict a poorer response to treatment. This effect is probably related to the lack of statistical power to detect these differences in a group in which the low number of previous SRI trials was a distinguishing characteristic. Certainly, previous positive studies in this area have used relatively more refractory groups based on the number of previously failed SRI trials. Taken together with the first point above, we suggest that future work in this area should consider longer periods at maximum tolerated doses of SRI's prior to categorisation of subjects as treatment refractory.Third, the use of a slow up-titration resulted in a relatively low mean daily dose being administered for the majority of the study. For instance, a mean daily (week 6) dose of 168 mg/day in the quetiapine group (median 175 mg) had only been achieved for the final two weeks of the study. These doses are comparably low to those used in the negative single-blind study using low dose quetiapine by Sevincok et al . In contFourth, the impact of repeated clinical assessments and rating of relatively small changes in clinical severity combined with regular dose increases, may conceivably have increased the placebo response rates resulting from increased optimism, a tendency to over-report improvements and belief that higher doses are more likely to be more effective than lower doses. This may be particularly true for the placebo-treated group that were considerably less likely to report sedation as an adverse event and as such were more likely to have their treatment dose increased at each visit. Our results differ, with respect to placebo response, from a considerable literature that suggests a consistently lower placebo response rate in treatment trials in OCD than in other mood and anxiety disorders. While we believe that the reasons (1–3) discussed above probably provide the main reasons for our finding, the impact of repeated assessments and the potential effect thereof cannot be entirely discounted.Despite significant improvement in each of the study groups, response to quetiapine augmentation in SRI non-responders, failed to separate from placebo treated subjects at the end of the six week treatment phase. A number of limitations in study design make comparisons with previous studies in this area difficult and probably contributed to our negative findings. Future work in this important clinical area should address these limitations.Dr. Stein has received research grants and/or consultancy honoraria from Astrazeneca, Eli-Lilly, GlaxoSmithKline, Lundbeck, Orion, Pfizer, Pharmacia, Roche, Servier, Solvay, Sumitomo, and Wyeth.PDC drafted manuscript and analysed data, BV protocol design, SS protocol design, JEM drafting of manuscript, statistical design, data acquisition, MVM protocol design, DJS principal investigator, protocol design, drafting of manuscript.The pre-publication history for this paper can be accessed here: