Currently, several systems have been proposed to classify viruses and indicate the relationships between different ones, though each system has its limitations because of the complexity of viral origins and their rapid evolution rate. We hereby propose a new method to explore the relationships between different viruses.A new method, which is based on the virus-host protein-protein interaction network, is proposed in this paper to categorize viruses. The distances between 114 human viruses, including 48 HIV-1 and HIV-2 viruses, are estimated according to the protein-protein interaction network between these viruses and humans.The results demonstrated that our method can disclose not only relationships consistent with the taxonomic results of currently used systems of classification but also the potential relationships that the current virus classification systems have not revealed. Moreover, the method points to a new direction where the functional relationships between viruses and hosts can be used to explore the virus relationships on a systematic level. Viruses can be classified according to different aspects ,2, such Phaginae (attacks bacteria), Phytophaginae (attacks plants), and Zoophaginae  according to the host type. These classifications are accepted by some virologists, but not all the virologists are satisfied with the current virus classification systems [All of the three main classification systems mentioned above, the Baltimore classification, LHT System, and Casjens and Kings Classification, are based on certain chemical or physical characteristics of viruses. On the other hand, the ICTV classification system is based on the hypothesis that the members of the order might have a common ancestor. However, sixty-four of the total 84 families in the ICTV classification system are still unplaced. The Holmes classification sorts viruses into  systems . Some of systems , it is hA virus needs to use the DNA replication and protein synthetic systems of its host to complete its life cycle and proliferation. Therefore, some viruses exhibit strong co-evolutionary relationships with their mammalian host organisms ,13. The Our method based on the virus-host protein-protein interaction network has shown us the relationships among different viruses according to molecular function. As it was demonstrated in the molecular function tree Figure , 114 virExamination of HIV classification using our method reveals additional insights. HIV has two subtypes, HIV-1 and HIV-2, which are extracted from chimpanzees and sooty mangabeys respectively . Both suIn evolution research, different indicators, such as the similarity between conserved sequences, have been used to determine the distances between organisms. In our method, we have defined the smallest special score derived from the SSBP of proteins between two sets as the distances between different viruses. The mathematical definition of the distance between two sets is the infimum of the distance between any components of the two sets. Our definition of the distance between two viruses is consistent with the mathematical distance definition of two point sets. Moreover, some human proteins, with which a viral protein interacts, could exert their function in relatively general processes. These general proteins contribute less to differentiate viruses. In an ideal situation, we should use the proteins that have more specific functions and participate in more special processes to reflect the relationship between different viruses. The infimum represents the most specific similarity between two protein sets and could reflect the relationship between two viruses on the most specific level. Considering the definition of GO term is at a general level, the smallest special score also has the tendency to get rid of the non-specificity of some GO terms in our sets.In our new approach, the ability to detect the relationship between distinct viruses relies on the quality of the virus-host protein-protein interaction network explicitly. If the network is reliable and contains enough information to bridge the connection between viruses and their hosts, the relationship disclosed based on PPI network would reveal more functional associations to the virologists who are interested in the relationships between different viruses. In total, 9683 human proteins are confirmed to interact with these viral proteins of 114 viruses, and among them 8249 human proteins are verified to interact with 48 HIV viruses, while 66 non-HIV viruses correspond only to 1434 human proteins. This number is relatively low compared to the number of human proteins that interact with HIV proteins. As discussed above, the classification of HIV viruses displayed much more reliable result than for the rest groups of the viruses. This might be caused by the difference between the amounts of data in the two corresponding datasets that are currently available. It is expected that more verified virus-host protein-protein interaction data of other viruses may lead to more reliable and valuable results for exploring potential relationships between distinct viruses. Our method points to a new direction to elucidate the relationship between viruses on the systematical level and provides rich information for virologists to study the relationships among various viruses.http://molvis.vbi.vt.edu/pig/index.php) describing the pathogen and human protein-protein interaction. We combined the data from the two sources mentioned above to build the protein interaction networks between each virus and its host, human, in our paper. Each interaction pair in the network is composed of a viral protein and a human protein. This network is the foundation that we used to evaluate the relationships between different viruses. The distance between distinct viruses is calculated according to the functional similarity of the host protein that interacts with the corresponding viral protein in the network. In the GO system, each human protein has been normally assigned GO terms in three different categories - 'Cellular Component', 'Biological Process' and 'Molecular Function', we used the GO term - "Molecular Function" to carry out the analysis since researchers usually are more interested in the molecular function of a protein when they study the virus and host interaction.The protein-protein interaction network used in this paper is constructed mainly according to the results of Dyer et al. , which fAs some viruses exhibit co-evolution with their host ,13, asseThe distance between two sets C and D is defined as:The method of smallest shared biological process, which is used to measure the functional similarity between different proteins in the previous work ,25, is tThe authors declare that they have no competing interests.Data collection: FX. Programming: FX, CZ, LJ. Design of the analysis process: TLS, YD and FX. Data analysis: FX, LJ, TLS. Paper Writing: FX, YHL, TLS.This file contains the GO terms of human proteins that correspond to separation of HIV-1 and HIV-2.Click here for fileTree files based on the GO terms of "Biological Process", "Cellular Component" of HIV and all of the viruses in our network have been stored in this supplementary file. These tree files can be viewed with the help of "treeview" and other similar software.Click here for file


Critical Assessment of Techniques for Protein Structure Prediction (CASP) rounds 9 and 10. A web server for the approach is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/SAFrag.Predicting accurate fragments from sequence has recently become a critical step for protein structure modeling, as protein fragment assembly techniques are presently among the most efficient approaches for de novo prediction. A key step in these approaches is, given the sequence of a protein to model, the identification of relevant fragments - candidate fragments - from a collection of the available 3D structures. These fragments can then be assembled to produce a model of the complete structure of the protein of interest. The search for candidate fragments is classically achieved by considering local sequence similarity using profile comparison, or threading approaches. In the present study, we introduce a new profile comparison approach that, instead of using amino acid profiles, is based on the use of predicted structural alphabet profiles, where structural alphabet profiles contain information related to the 3D local shapes associated with the sequences. We show that structural alphabet profile-profile comparison can be used efficiently to retrieve accurate structural fragments, and we introduce a fully new protocol for the detection of candidate fragments. It identifies fragments specific of each position of the sequence and of size varying between 6 and 27 amino-acids. We find it outperforms present state of the art approaches in terms (i) of the accuracy of the fragments identified, (ii) the rate of true positives identified, while having a high coverage score. We illustrate the relevance of the approach on complete target sets of the two previous  Due to the large number of available protein structures and progress in remote homology detection, protein structure modeling is progressively focusing on smaller and smaller parts of protein structure de novo modeling has also come from fragment assembly techniques - see for instance The search for short candidate fragments matching a sequence has been tackled within different contexts. Firstly there is interest in analyzing the structure/sequence relationship at the local level, as pioneered by Rooman and Wodak in the early 90′sThe identification of candidate fragments starts from a given amino acid sequence. Different strategies have been described, considering fragments of fixed or variable length, considering gaps or not. I-sites predicted structural alphabet profile. In previous studies, we have shown such prediction can be used to enhance protein domain fold attribution from sequence compared to other approaches using features derived from amino acid profiles de novo approach to peptide modeling A structural alphabet can be seen as a generalized secondary structure description allowing to label more accurately local conformations in the structures. Here, we use a Hidden Markov Model derived structural alphabet of 27 states - or structural alphabet letters - that describes the proteins as series of overlapping fragments of 4 amino acid length We have developed a new protocol to identify candidate structural fragments given the amino acid sequence of a query. At each position of the sequence, it searches for candidate structural fragments of variable length by mining a bank of structures. The search is performed for each query sub-sequences of size between 6 and 27 amino acids, presently using a brute force strategy: for each sub-sequence, a systematic scan of all proteins in the bank is performed, sliding the sub-sequence at each position of each protein, not allowing gap, and scoring the similarity. The scoring is based on the comparison of the structural alphabet profile of the sub-sequence with that of the protein scanned, using the Jensen Shannon divergence. A flowchart of the complete approach is presented We first assess the effectiveness of the profile-profile scoring to identify candidate fragments. The profiles correspond to the predicted probabilities that the sequence of each fragment of 4 amino acids adopts one of the conformations of the structural alphabet. The distance between two profiles is measured using the maximum Jensen Shannon  and correspond to irrelevant matches. For the alpha helical fragment, an additional area of strong density is observed for cRMSD close to 2Å. It corresponds to the alpha helices of the dataset, the 2Å deviation coming from the non helical C-terminus of the query. The third region observed for cRMSD close to 1Å corresponds to the true hits. Its absence for the beta hairpin is only apparent and results from a threshold effect in the iso contours, as can be seen looking at individual dots in the regions of low MJS and low cRMSD. Compared to a helical fragment, fewer hits are expected for a beta hairpin because the larger conformational stability of a helical fragment compared to that of a beta hairpin makes the expected number of very low cRMSD fragments larger for helical conformations. Thus, for both cases, low de novo modeling of peptides A second observation is that a rather large range of Since it is hard to assess the exact amount of cases that could be attributed to each of the aforementioned explanations for having fragments of low cRMSDs but large correct fragments upon all fragments returned, that should be as high as possible. Consequently, means to control the expected precision of the protocol are important. To this respect, looking at a posteriori precision.We now consider a second important condition for efficient structural fragment identification. The approach should return as few erroneous fragments as possible, where erroneous means a fragment adopting an incorrect conformation that will lead to poor modeling. This can be measured as the precision of the approach, i.e. the ratio of the The analysis of the performance of the complete protocol is summarized in To investigate if the protocol can take advantage of mining closer homologs, we have also performed a similar experiment using a subset of the Protein Data Bank filtered at 50% sequence identity (PDB50). The added value of using structural alphabet profiles can be discussed by comparing our procedure (SA-Frag) with HHfrag, an approach based on amino acid profile comparison recently reported to outperform other approaches such as nnmake We have also assessed the relative performance of both approaches on the very recent CASP10 target set. Considering all the targets, the performance of both approaches appears rather stable over CASP9 and CASP10 target sets. As for the CASP9 targets, Finally, we have also considered combining the hits returned by HHfrag and SA-Frag. The results are reported In the present study, we have introduced a new approach for the identification of candidate fragments, based on the comparison of structural alphabet profiles predicted from the amino acid sequence.de novo prediction approachAs a more detailed characterization of the local structure of proteins compared to the classical secondary structure conformations Among the possible reasons for such improvement, the main one is that predicted structural alphabet profiles directly code for local conformation information, a difference with amino acid profiles. Since structure is known to be more conserved that sequence, such encoding could be more relevant, and our previous results about fold attribution Another explanation could be that the higher dimension of the profile - 27 here - could help to grab some accurate details of the local sequence - structure relationship. Following, one could ask how the choice of the collection of canonical local conformations impacts the results. Interestingly, the protocol described here is not specific of the particular structural alphabet used, and indeed, numerous collections of short fragments - denominated as structural alphabets or not - have been described by other groups  corresponds to the 4 678 proteins used by We describe the protein structures using a Hidden Markov Model derived structural alphabet of 27 letters Starting from an amino acid sequence, the SA-profiles are predicted using a protocol identical to that described in The comparison of the predicted SA profiles is performed assuming an ungapped procedure. In our experience where M is where P(i) is the probability of SA letter For two vectors of profiles of size where Given a query of size Since the number of hits can be very large , the search procedure embeds two mechanisms to limit their number. Firstly, for each query, we limit the number of hits to the first N best hits, in practice 500. Secondly, the N best hits are sorted according to their A last filtering step is achieved by considering the expected precision of the candidate fragments. All hits associated with an expected precision more than an upper threshold are kept, and those with an expected precision less than a lower threshold are discarded. Fragments having an expected precision in between these two thresholds are used as best candidates for regions not yet covered. Since these fragments are associated with a less predictable quality, we accept some redundancy in these regions. In practice, it is possible to adjust the values depending on the desired ratio between coverage and precision. In this study, we used upper and lower values of 0.99 and 0.82 (resp. 0.995 and 0.65) with the PDB25 (resp. PDB50) set. Nested hits from the same protein are discarded.To assess the results, we define true positives (TP) the hits deviating from the query by less than a given cRMSD. Since the distribution of the cRMSD over random fragments depends on fragment size, we follow the rule used in


This paper proposes a new omni-directional electromagnetic acoustic transducer (EMAT) for the ultrasonic Lamb wave (ULW) tomography imaging (TI) of defects in metallic plates. The proposed EMAT is composed of a permanent magnet and a coil with a contra-flexure structure. This new EMAT coil structure is used for omni-directional ULW transmission and reception and ULW TI for the first time. The theoretical background and the working principles of this EMAT are presented and analyzed. The experimental results of its use on a 3 mm thick aluminum plate indicate that the EMAT with a contra-flexure coil (CFC) can transmit and receive a pure single A0 mode ULW with a high signal-to-noise ratio (SNR). Thus, the extraction of the projection data used for ULW TI may be performed accurately. The circumferential consistency of the projection data is only slightly influenced by the distortion of the eddy current field that is induced by the new CFC with an irregular shape. When the new EMAT array is used for ULW TI using the cross-hole method and SIRT arithmetic, a desirable imaging quality can be achieved, and the estimated size of an artificial corrosion defect agreed well with its actual value. The relation between the reconstruction resolution and the number of the new EMATs used is analyzed. More TI experiments are carried out when the aluminum plate defect is in two different locations relative to the EMAT array, for the further investigation of the performances of the new EMATs. During production and utilization, these metallic plates will inevitably acquire a number of defects that can cause serious, adverse influences on the safe service of the facilities and equipment made from them. Therefore, these metallic plates must be timely and efficiently inspected. Relative to the traditional inspection methods of point-by-point scanning, ultrasonic Lamb wave (ULW) inspection technology allows for a line with long distance to be scanned after a single excitation. Because the ULW inspection technology also has the advantages of being fast and efficient during an entire volumetric inspection –4, it iset al.  can be determined. This result indicates that under the same distance L, a better reconstruction resolution can be obtained by increasing the number of the EMATs, according to the requirements of practical applications.High construction resolution and fewer artifacts for ULW TI are always desired in practical applications . In the 4.The non-contacting, omni-directional EMAT is an ideal choice for the ULW TI of the defects in metallic plates. In this paper, a new omni-directional ULW EMAT composed of a CFC and a permanent magnet was proposed. The theoretical analysis and experimental results indicate that by using the new CFC EMAT, a purer single A0 mode ULW with a higher SNR could be transmitted and received, and the extraction of the projection data for TI could be performed more accurately, compared to the traditional CWSC EMAT. Although the proposed CFC with the irregular shape induces a distortion of the eddy current field in aluminum plate, the circumferential consistency of the TOF projection data is only slightly influenced. The experimental results of imaging an artificial defect in 3 cm thick aluminum plate indicate that the new EMAT array has an acceptable ULW TI performances, and can accurately locate and determine the size of the defect when the defect is in different locations relative to the EMAT array. Moreover, according to the analyzed result, the reconstruction resolution can be improved by increasing the number of the new EMATs used, according to the requirements of practical applications.


Health state valuation exercises can be conducted online, but the quality of data generated is unclear.To investigate whether responses to binary choice health state valuation questions differ by administration mode: online versus face to face.Identical surveys including demographic, self-reported health status, and seven types of binary choice valuation questions were administered in online and computer-assisted personal interview (CAPI) settings. Samples were recruited following procedures employed in typical online or CAPI studies. Analysis included descriptive comparisons of the distribution of responses across the binary options and probit regression to explain the propensity to choose one option across modes of administration, controlling for background characteristics.Overall, 422  respondents completed a survey. There were no overall age or sex differences. Online respondents were educated to a higher level than were the CAPI sample and general population, and employment status differed. CAPI respondents reported significantly better general health and health/life satisfaction. CAPI took significantly longer to complete. There was no effect of the mode of administration on responses to the valuation questions, and this was replicated when demographic differences were controlled.The findings suggest that both modes may be equally valid for health state valuation studies using binary choice methods . There are some differences between the observable characteristics of the samples, and the groups may differ further in terms of unobservable characteristics. When designing health state valuation studies, the advantages and disadvantages of both approaches must be considered. To conduct health state valuation studies, a range of administration modes can be used. These include face-to-face interviews using paper-and-pencil methods, face-to-face interviews using computer-assisted personal interviews (CAPIs—in which surveys are displayed via a computer interface while an interviewer is present), and online studies. To date, face-to-face interviews using paper-and-pencil methods have been the most widely used mode for collecting health state valuation data and were used to derive preference weights for EuroQol five-dimensional (EQ-5D) questionnaire using the time trade-off (TTO) preference elicitation technique Each mode has advantages and disadvantages that may affect the data generated and therefore need to be considered in the design of health state valuation studies. Face-to-face interviews may provide high-quality data with good completion rates and reliability Studies have compared the online and CAPI administration of health state valuation exercises. Comparisons of the online and face-to-face administration of iterative person trade-off (PTO) tasks have found broadly similar results across modes TTO, where duration is included as a dimension alongside the health state classification system, can be used to value health states at the aggregate level In addition, it has not been established whether responses to binary choice health state valuation questions are comparable across administration modes. Binary choice questions such as DCECollecting data online raises concerns about the representativeness of the sample and comparability with data collected by using other methods. Samples recruited online may be biased in terms of unobserved characteristics This study aimed to compare responses to binary choice versions of health state valuation questions across online and CAPI modes of administration. This was done by administering identical surveys where the only difference was the mode of administration used to collect the data. We hypothesized that the responses to different types of binary choice valuation questions do not differ across modes. To investigate issues around the representativeness of samples recruited for face-to-face and online studies, we also compare the demographic characteristics and self-reported health status of the samples and those of the general population.TTO). Not all the attributes above vary across each question . The health states used were based on the EQ-5D-5L The online survey had 15 versions, most of which contained only three of the seven types of questions. One version, however, contained all seven question types, and this is used in the study reported here. The CAPI survey matched this particular online version in terms of questions and sample size. In other words, the data used in this comparison study have a wide coverage of question type, but it is not intended that they are used to address any of the methodological issues themselves. In this version, 12 questions were administered across three question modules (the time taken to complete each module was recorded). Module 1 included five type I questions, module 2 included one of the question types II–VI , and module 3 included two DCEEach survey began by providing study information, and this was followed by a compulsory informed consent page. Respondents were then asked a series of demographic questions and completed self-reported health status , health and life satisfaction questions , and the EQ-5D-5L before completing the 12 binary choice valuation questions.To achieve a comparison of the two modes of administration as they would happen in the real world, the CAPI and online samples were recruited separately following procedures employed in typical surveys.For the online survey, respondents were sourced from an existing Internet panel and were selected following set quotas based on the UK general population across five age groups—18 to 24, 25 to 34, 35 to 44, 45 to 54, 55 to 64—and sex. Invitations were sent out via e-mail. Potential respondents were screened out before starting the experimental questions if the relevant quota for age and sex was already complete or after the completion if they completed the survey in less than the minimum imposed time limit of 5 minutes . The online survey described in this study was 1 of 15 different online surveys that aimed for an overall achieved sample of 3000 (∼200 respondents per version). The questions included in the version described here were identical to those used in the CAPI survey, and therefore a subset of respondents from the overall sample is considered in this study.For the CAPIs, recruitment followed set quotas for age and sex based on the UK general population and scaled down for an achieved sample of 200. This attempted to ensure the overall comparability of the sample characteristics across the administration modes. Participants were recruited by knocking on 1 in every 10 doors in randomly selected postcodes in five UK areas. The survey was presented to respondents on a laptop, and the interviewer read out all the questions and text on the screen and recorded the response given by the respondent. This was done in a one-to-one setting. The same minimum completion time of 5 minutes was imposed, and participants were able to stop the survey at any time.U analysis, and analysis of variance. The background characteristics of the overall, CAPI, and online samples were also compared with the general population of England and Wales by using statistics extracted from the 2001 UK census P values less than 0.05.Background characteristics, self-reported health status, and time taken to complete the survey were compared across the two samples by using chi-square analysis, Mann-Whitney Comparisons of the proportions of respondents choosing scenario B using a range of completion time cutoff points  were also investigated by using chi-square analysis. We also compared the responses for different groups of respondents defined by the time taken to complete each of the three binary choice question modules. Two groups were defined for each module: group 1 included those completing the module in less than the median time taken to complete the module  and group 2 included those completing the module in more than or equal to the median time taken to complete the module . The median time was used as the cutoff to allow for a reasonably equal split between the groups.βi s are the parameters to estimate; D represents the sociodemographic characteristics of respondents; S represents health satisfaction of the respondent; X represents the properties of the health state using health state (H), duration (T), lead time in full health (L), person perspective (P), and satisfaction level (S)  is the distribution function of the standard normal distribution P less than 0.05 and P less than 0.01 are reported.Probit regressions were used to explore the determinants of the propensity to choose scenario B for each question: (S) see ; M repreIn total, 422 respondents completed either the online survey or the CAPI version. For the online survey, 2326 panel members were invited to take part and 487 potential respondents (20.1%) accessed the survey. Of these, 266  were screened out because they belonged to a completed age and sex quota , left the survey during completion , or completed the survey in less than 5 minutes . This group was defined as noncompleters. In total, 221  fully completed the survey in 5 minutes or more. There were no significant age or sex differences between the responder and nonresponder samples.The CAPI version was completed by 201 respondents. Information about the response rate for the survey is not available, because it was not recorded by the survey company, and therefore the response rate cannot be calculated. Nevertheless, in a similar CAPI study using the same methodology as part of the PRET project, Mulhern et al P<0.001). The online sample is more similar to the general population in terms of marital status than the CAPI sample (with more of the CAPI sample being married or with a partner). The overall education level of the CAPI sample, however, is more similar to that of the general population.There were no significant differences between the online and CAPI groups by age and sex, but a number of demographic variables significantly differed between the samples . These iTTO questions) was not significant. Across all three modules, the SD of the time taken is longer for the online sample than for CAPI sample. In terms of the median completion times, the CAPI sample took significantly longer to complete the overall survey, background questions, and all three experimental question modules  and module 2 (one of the types II–VI binary choice questions). The difference between the samples for the time taken to complete module 3 (two DCEules see .P<0.001), higher levels of health satisfaction (P<0.001), and higher levels of life satisfaction (P<0.001). The mean EQ-5D-5L index score for the online sample  = 18.66; P<0.001). EQ-5D-5L dimension responses also differ significantly by administration mode except mobility, with the CAPI group reporting less problems.Responses to the self-report general health and health and life satisfaction questions are displayed in TTO questions) did not significantly differ by administration mode for any of the seven binary choice question types  that found differences between online and face-to-face responses and concluded that this was due to the iterative nature of the process The finding of equivalence across modes of administration is valid for samples recruited following the standard procedures for CAPI  and online  who were found to have similarities with the general population . This suggests that our findings are relatively robust. We have been unable, however, to assess the consistency of the results by using overall time cutoff points below 5 minutes, and this limits the wider applicability of the findings to binary choice valuation studies conducted online that do not impose minimum completion times. Future research may investigate respondent engagement in the online environment in more detail, for example, by analyzing responses using a wider range of minimum time limits, recording the time taken to complete each task, or developing innovative methods for presenting the tasks.There have been concerns about the representativeness of online samples and how this might affect the comparability of results across samples We were not able to assess how the mode of administration affects the responses of those older than 65 years, because this group was not included in the sampling frame for the study. This potentially limits the applicability of our findings, as the Office of National Statistics predicts that approximately 59% of the adults 65 years or older use the Internet every day or almost every day (in comparison to ∼80% of those aged 18–54 years and 75% of those aged 55–64 years) It is in theory possible to make two samples agree in terms of any observable characteristic. Nevertheless, even with highly selective screening, the samples may differ in terms of further unobserved characteristics. The CAPI sample characteristics are influenced by who is at home when the interviewer visits, who agrees to take part, and who completes the interview. The online sample using an Internet panel is affected by who has access to the Internet, who is a member of the online panel, who in the panel agrees to take part, and who of those agreeing to take part completes the survey. It is not clear how the different selection mechanisms affect unobservable sample characteristics and therefore responses to health state valuation questions. Not everyone is equally likely to join an online panel and complete a particular survey or take part in a face-to-face interview. Typically, characteristics of nonresponders to interviews are not available, and one advantage of online surveys using existing Internet panels is that certain characteristics of nonresponders may be accessible. This allows for further insight into issues around nonresponse. A related issue is comparing the overall response rates for each mode of administration. Unfortunately, this study cannot inform this issue as the number of people who were invited to take part in the face-to-face CAPI study was not recorded by interviewers.When designing health state valuation studies, the financial and time costs of the surveys are important and must be considered in light of the available preference elicitation methods and the modes available for administering the techniques. The cost of any survey has a fixed element and is not completely proportionate to the sample size. Nevertheless, even if generalized cost estimates cannot be given, it is generally the case that face-to-face interviews are substantially more costly per respondent and may take a much longer time to recruit sufficient numbers of participants. At the same time, any survey is only as good as the quality of the sample, and therefore the quality of the Internet panel needs to be scrutinized: one way to do this may be to look at how panel members are recruited and what incentives are offered. Overall, when the survey design is amenable to online administration, the incremental cost-effectiveness of conducting interview surveys must be examined.TTOThis article discusses the findings from a head-to-head comparison of online and CAPI administrations of binary choice health state valuation questions. The two administrations have different advantages and disadvantages, and the two samples significantly differ across selected background characteristics, but the similarities with the general population indicate that the standard sampling frames used for face-to-face and online research studies are both valid. Responses to the main experimental binary choice questions, however, were not significantly different across the modes, and the mode of administration was not a significant factor explaining the responses. Therefore, both modes produce comparable data, and both can be used to administer health state valuation surveys including binary choice valuation questions such as DCE


Prenatal diagnosis of β-thalassemia was accomplished for the first time in the 1970s by globin chain synthesis analysis on fetal blood obtained by placental aspiration at 18–22 weeks gestation. Since then, the molecular definition of the β-globin gene pathology, the development of procedures of DNA analysis, and the introduction of chorionic villous sampling have dramatically improved prenatal diagnosis of this disease and of related disorders. Much information is now available about the molecular mechanisms of the diseases and the molecular testing is widespread. As prenatal diagnosis has to provide an accurate, safe and early result, an efficient screening of the population and a rapid molecular characterization of the couple at risk, are necessary prerequisites. In the last decades earlier and less invasive approaches for prenatal diagnosis were developed. A overview of the most promising procedure will be done. Moreover, in order to reduce the choice of interrupting the pregnancy in case of affected fetus, Preimplantation or Preconceptional Genetic Diagnosis (PGD) has been setting up for several diseases including thalassemias The late gestational age in which fetal diagnosis was carried out, the risk of misdiagnosis due to a not clear cut-off between some heterozygotes and affected fetuses, the high risk of miscarriage due to the sampling procedures, made indeed the procedure difficult to accept from the couples.The continuous advances in the knowledge of the molecular pathology of the disease, the discovery of restriction fragment length polymorphisms (RFLP) linked to the β-like globin gene, the development of methodologies for mutation detection and the application of the villocentesis for the recovery of nucleated fetal cells, allowed a fast improvement both in feasibility and acceptability of prenatal diagnosis. For a short period, in the eighties, the diagnosis of thalassaemia was obtained either indirectly by linkage analysis using RFLP at the β-globin gene clusterIn this review we will delineate current procedures for prenatal and preimplantation diagnosis of thalassemias as well as the most promising approaches for non-invasive prenatal diagnosis.Definition of molecular defect in both parents is a prerequisite for prenatal diagnosis of the disease.The majority of defects affecting the β-globin gene are point mutations that occur in critical areas for its function, or single/few base addition/deletion that change the frame in which triplets are translated into protein. Very rarely β-thalassemia results from gross rearrangement in the β-globin gene cluster. In spite of the marked molecular heterogeneity, a limited number of molecular defects are prevalent in every at risk population. This may be very useful in practice, because a panel of most frequent mutations to be searched for can be designed according to the carrier’s ethnic origin. 9Known mutation detection is carried out by a number of PCR-based techniques. Among them, the most commonly used are the primer-specific amplification  and the reverse oligonucleotide hybridisation with specific oligonucleotide probes .The method is based on the principle that a primer carrying a mismatch in its 3’ region cannot anneal on its template. With this method, the target DNA fragment is amplified in two separate PCR reactions using a common primer and either of the two following primers: one complementary to the mutation to be detected  and one complementary, at the same position, to the normal DNA . Normal DNA is amplified only by the normal primer while DNA from homozygotes only by the β-thalassemia primer and DNA from heterozygotes by both primers. A different sized fragment of the β-globin gene is simultaneously co-amplified as an internal control of the PCR reaction.When the spectrum of mutations to be searched is complex, ARMS is not the most appropriate method. In this case RDB results to be more informative and efficient. The method uses membrane-bound allele-specific oligonucleotide probes that hybridize to the complementary sequence of the PCR product prepared using patient DNA as starting template.Several other methods have been developed to search for known mutations, i.e. oligonucleotide ligation assay,In recent years a real time PCR assay has been successfully applied to both carriers screening and prenatal diagnosis.Technically, we can realistically predict further simplification and fully automation of the procedures for the detection of the β-thalassemia mutation in carrier screening and prenatal diagnosis. Nowadays a number of systems for molecular detection of the β-thalassemia mutations is commercially available, which are not completely automated and quite expensive. Among them, the oligonucleotide microchip based-assays have been proposed many times for the large-scale detection of mutations in genetic diseases, including β-thalassaemia.When carriers escape to the above mutation detection approaches, further investigations need to be carried out by alternative methods which uncover the presence of unknown mutations by scanning the whole gene. Denaturing gradient gel electrophoresis (DGGE),If a mutation is not detected by sequence analysis, we search for the presence of small deletions by polyacrylamide gel electrophoresis of amplicons designed for the most frequent small deletional defects of the β-globin gene (gap PCR). Furthermore, the presence of larger deletions of the cluster may be identified by Southern-blotting or more recently by Multiple Ligation-dependent Probe Amplification (MLPA) for which a commercial kit is available (SALSA MLPA KIT P102 HBB-MRC Holland).In a very limited number of cases, direct sequencing from position -600 to 60 bp downstream from the β-globin gene and methods for deletion detection, failed to detect the disease causing defect. In these cases, the molecular defect may reside either in the locus control region of the β-globin gene cluster, or in one of the genes, outside the β-globin gene region, encoding for regulatory proteins acting in trans on the function of the β-globin gene. Very recently it has been proved that the β-thalassaemia like phenotype could be caused by the coinheritance of a β-globin gene defect and a duplication of the α- globin gene cluster, which results in an excess of α chain. In these selected cases, the characterization of these α-globin gene rearrangements (SALSA MLPA KIT P140-B2 HBA-MRC Holland) can be routinely carried out with success by MLPA analysis.Both members of the couple at risk are counseled in a non directive way. The nature of the disease, the implications of being carriers and the reproductive choices are analyzed, specifically those concerning birth control, including prenatal or preimplantation diagnosis and the possibility, in case of affected fetus HLA compatible, to not interrupt pregnancy As for fetal testing, detailed information is offered regarding the risk of fetal mortality, the risk of misdiagnosis, and the mortality and morbidity of an abortion in case of affected fetus.Fetal DNA for analysis can be obtained from either amniocytes or chorionic villi. At present the most widely used procedure is chorionic villi sampling, because of the clear advantage of being carried out during the first trimester of pregnancy, generally at the 10th–12th week of gestation.Samples obtained by villocentesis need to be accurately dissected under inverted microscope in order to remove maternal decidua, that represent the major cause of diagnostic error in prenatal diagnosis of monogenic diseases,Fetal DNA is analysed using the same methods described above for the detection of known mutations during carrier molecular screening. To limit the possibility of misdiagnosis, we analyse chorionic villous DNA with two different procedures: i.e. RDB hybridisation and primer-specific amplification, using distinct couples of primers.Misdiagnosis may occur for several reasons: failure to amplify one copy of the target DNA fragment, mispaternity, maternal contamination, and sample exchange. Misdiagnosis for failure of DNA amplification is obviously limited by the double approach described above. To avoid misdiagnosis due to maternal contamination as well as mispaternity and/or sample exchange, a fetal DNA microsatellite analysis is usually performed to verify the presence of one allele from each parent.Currently, prenatal diagnosis is a widely applied and well accepted procedure. Among the patients screened we have found an acceptability of 99,3% for early prenatal diagnosis by CVS. This data, if compared with previously utilized procedures such as fetal blood sampling, with an acceptability of 93,2%, and 96,4% by amniocentesis, demonstrates how the acceptance of the procedure depends on its precocity.22The screening program in the Mediterranean countries have proven to be very successful in reducing the number of thalassemia patients. In Sardinia, thalassemia major was present in 1 in 250 births, and has declined to 1 in 4000 births . Other cThe progress in assisted reproduction and molecular genetics techniques, particularly the advent of PCR that has made possible to analyze the genotype of a single cell, has paved the way for preimplantation genetic diagnosis (PGD).25This technique was introduced as an option for avoiding the decision to terminate an established pregnancy diagnosed as affected by conventional approaches.The term preimplantation genetic diagnosis describes those procedures which involve the removal of one or more nuclei from ovocytes (polar bodies) or embryos (blastomeres of trophectoderm cells) to test for mutation in the target gene or aneuploidy before transfer.PGD requires that couples at risk undergo in vitro fertilization (IVF) even if not infertile and for this reason a multidisciplinary approach including an appropriate genetic counseling and the referral to both a fertility clinic and to a high specialized molecular genetics laboratory is mandatory.Counseling for couples considering PGD must include additional information regarding at least the risk associated with IVF procedures and with embryo biopsy, the technical limitations of DNA analysis, including the risk of failure of the procedure as well as that of misdiagnosis, and the need of subsequent prenatal diagnosis to confirm the result. Beyond that, the possibility that no embryos may be transferred and the dispositions of embryos not transferred have also to be seriously considered.Preimplantation may be carried out by either cleavage-stage biopsy of 1–2 blastomeres, from an eight-cell embryo three days after in vitro fertilization carried out by ICSI (Intracytoplasmatic Sperm Injection), or by the biopsy of polar bodies.For cleavage-stage biopsy the embryo is grown in vitro until it reaches a six-eight cell stage, which usually occurs on the third day after insemination. Polar bodies diagnosis, pioneered by Verlinsky and his group in ’90,Blastocyst biopsy, even if it has the advantage to provide a higher number of cells,, is at present more rarely used because of the difficulties of the embryos to reach this stage in IVF programs.The cleavage-stage biopsy of blastomeres from a eight-cell embryo is the most frequently used PGD procedure all over the world.Methods for mutation detection in PGD are always based on multiple steps of PCR. Mutations are detected in PCR products by various methods that combine speed, analytical sensitivity and specificity. In particular, a first round of multiplex PCR is performed to amplify both the β-globin gene region including the mutation and one or more polymorphic loci. Secondly, two separated nested PCR reactions are performed to amplify the two or more selected genomic regions. Finally, the polymorphic alleles are directly detected by capillary electrophoresis of the amplified fragment, while the presence of β-globin gene mutations are identified by a subsequent minisequencing reaction.For both techniques a prenatal diagnosis by villocentesis is recommended in order to avoid diagnostic errors.Successful pregnancies following the transfer of human embryos in which the β-globin gene defect has been excluded, occur only in 20–25% of cases and the birth rate of a child is even lower. Due to the low birth rate most women have to undergo PGD several times in order to give birth to a healthy child.30Transfer of no more than 1–2 embryos is strongly recommended in order to avoid multiple pregnancies.32Among clinical geneticists there have been much discussion about the main goal of PD. Some have argued that the main aim is to avoid the birth of an affected child. Others have emphasized the reproductive confidence and the purpose of informing couple at risk about the status of the fetus. Several studies indicate that if there is no PD option, a large proportion (up to 50%) of the couples at high risk of an affected child refrain from pregnancy despite their wish to reproduce. When PD is possible many more at-risk couples dare to embark on a pregnancy.Most experts consider PGD as an additional option for couples at risk and not as a replacement for conventional prenatal diagnosis. PGD is still considered a highly specialized experimental procedure with limited results, mainly dedicated to couples against abortion for ethical and religious reasons and to a small proportion of couples, who have experienced repeated abortion, that ask for referral for this procedure.At present its use in routine monitoring of pregnancies at risk is precluded by the technical demand for these procedures, the difficulty in organizing the service, and the high costs.Simplification of preimplantation and preconception genetic diagnosis, together with an increase in the pregnancy rate, may lead to a more extensive use of the procedure in the future.In the sections below the most significant studies, which have been carried out in this field of research, are briefly summarized. The most relevant results have been grouped in three different sections, according to the different cell type in which they have been acquired. A separate section is dedicated to the the NIPD of β-thalassemia.The first evidence that fetal cells circulate in maternal peripheral blood dates back to 1893 when George Schmorl observed the presence of placentally derived trophoblasts in the lungs of 17 autopsied women affected by severe eclampsia.33In 1959 Douglas36Trophoblast-specific cell-surface antigens have not yet been characterized and several experimental evidences have shown that the H315, initially described as the specific antigen for trophoblasts, is indeed adsorbed in maternal leucocytes.37www.safenoe.org).These are some of the reasons why, in recent years, trophoblasts are no longer considered as the best target cells for non invasive prenatal diagnosis. Nevertheless, this line of research has not yet completely abandoned as the characterization of trophoblast-specific antigens is one of the objectives of the SAFE  Network  gradient centrifugation step is carried out to remove non nucleated maternal erythrocytes. A schematic workflow resuming one of the strategies used for isolating fetal NRBCs from maternal peripheral blood is represented in Even with the high progress made in last twenty years in this field, the methods for erythroblasts enrichment are still limited as they mostly result in the recovery of fetal samples with low yield (FACS) and scarce purity (MACS), being variably contaminated by maternal cells.For these reasons in recent years several studies have been addressed to the proteomic field with the attempt to characterize novel fetal erythroblast cell-specific surface markers.For example, bi-dimensional electro-phoresis coupled with mass spectrometry has allowed the identification of 22 proteins, differentially expressed in sickle erythrocytes in comparison to healthy erythrocytes, and the detection of proteins up- or downregulated in fetal erythroid cells in comparison to their adult counterparts. Some of these results have been published as a full-patent application and the data concerning the new antibodies developed against these new targets expect to be validated in large samples of maternal blood.44In addition, further developments in fetal cells recovery are expected to be obtained through the application of micro-fluidic rare-cell capture technologies Despite the difficulties encountered to find the best target cell and the best method for their enrichment and isolation, several attempts have been made in last twenty years, to transfer the results of these researches into clinical practice. Unfortunately the lack of reproducibility of experiments hardly makes the isolation of fetal cells from maternal blood as a first choice method for NIPD of monogenic disorders. Below the most significative results obtained in NIPD of β-thalassemia are briefly summarized.The first example of non invasive prenatal diagnosis of haemoglobinopathies was described in 1990 by Camaschella et al.In those years most of the studies were addressed to couples carrying different mutations and only aimed to the exclusion of the paternal allele in the enriched fetal cells, as most of the times they were contaminated from maternal cells.In subsequent years, even if the fetal cells enrichment and selection methods have been greatly improved, other NIP diagnosis have been carried out but with fluctuating results. Below are described three significative examples of NIPD realized, with different level of success, by using single or pooled erythroid cells.In 1996 the group of Y.W.KanFew years later the group of Di NaroMore recently the group of KolialexiThe existence of cell-free nucleic acids within the human plasma was firstly reported in 1948 by Mendel and Metais51In 1997 Lo et al discovered for the first time that a fetus may release cell-free fetal DNA (cffDNA) into maternal plasma, thus providing an alternative to fetal cells for noninvasive prenatal diagnosis.52In recent years more information have been acquired about the concentration, the origin and the characteristics of the cell-free fetal DNA and several procedures have been developed in order to use it in prenatal diagnosis.The cell free DNA is constantly present in peripheral blood of non pregnant women and its concentration increases during pregnancy. The cell-free fetal DNA represent the 3–5% of the DNA present in maternal plasma from which, after delivery, it is rapidly cleared.Recent studies carried out by microfluidic digital PCR have revealed that cffDNA can be present at even higher concentrations which can reach up to 10–20% of total DNA in maternal plasma.Size-fractionation agarose gel electro-phoresis is one of the methods developed for fetal DNA enrichment and consists in the isolation of short-length DNA fragments (< 300 bp of length) which is the medium length of the cffDNA. This method coupled with the peptide-nucleic-acid clamp (PNA) PCR, which selectively suppresses the amplification of maternal alleles, and with the Allele-specific Real-Time PCR for mutation detection, has been used with success by Li et alMore recentlyNevertheless, for eventual future diagnostic application the protocol needs to be validated in larger sample, even if the high cost of the instrumentation required makes this platform difficult to apply in routine diagnostics and the size fractionation is considered an enrichment method more susceptible to maternal contamination.The use of peptide-nucleic-acid clamping to suppress the amplification of normal maternal alleles was firstly described by Cremonesi in 2004.Four years laterDespite its successfully application, this strategy, as the other above described technologies, is still restricted to couples which carry different mutated alleles and aimed to the detection of mutated paternal alleles.Another method recently described for NIPD of β-thalassemia is called APEX namely Arrayed Primer Extension. This is a mutation detection system which is based on the combined use of the microchip technology and the single nucleotide base extension method. This system has been recently described by the group of PapasavvaAs previously reported, one of the major problem which still limits the application of the described protocols in clinical practice is the impossibility to obtain highly purified fetal, cellular as well as cffDNA, samples which could allow the detection of parental alleles, even when they are identical. Few clinical applications of NIPD are actually restricted to the detection of the Y chromosome, for fetal sex determination, or the Rhesus D gene, in Rhesus D negative women, or, in general, of genetic loci which are absent in the maternal genome.In recent years a great improvement has been obtained in the field of the technologies which can explore the presence of sequence variations even in single molecules of DNA. The concept of “Digital PCR” was firstly in introduced in 1992 by Sykes59Recent applications of these technologies in the field of NIPD, and in particular in the diagnosis of aneuploidies and monogenic disorders, have shown that these methodologies may find useful application in the near future, even if several drawbacks need to solved and wider validation studied should be carried out before transferring their use in routine diagnostics.


The development of resistant strains of HIV is the most significant barrier to effective long-term treatment of HIV infection. The most common causes of resistance development are patient noncompliance and pre-existence of resistant strains. In this paper, methods of antiviral regimen switching are developed that minimize the risk of pre-existing resistant virus emerging during therapy switches necessitated by virological failure. Two distinct cases are considered; a single previous virological failure and multiple virological failures. These methods use optimal control approaches on experimentally verified mathematical models of HIV strain competition and statistical models of resistance risk. It is shown that, theoretically, order-of-magnitude reduction in risk can be achieved, and multiple previous virological failures enable greater success of these methods in reducing the risk of subsequent treatment failures. The development of multi-drug regimens for HIV therapy has resulted in HIV infection becoming a chronic, manageable disease in first world countries Mutation events in HIV replication appear to be dominated by point-substitution events, which occur with very high frequency. This, coupled with the high turnover rate of HIV in uncontrolled infection, create a situation in which multi-drug resistant virus develops frequently. When a resistant mutant emerges, it becomes necessary to switch to a new three-drug regimen, whose components exhibit no cross-resistance with the failed three-drug regimen Attempts have been made to re-sensitize the virus to previously failed regimens through the use of treatment interruptions; the theory is that the wild-type virus, which enjoys a competitive advantage in the absence of therapy, would re-establish dominance and potentially drive the resistant virus extinct through competition Attempts have also been made to use previously failed drugs in novel combinations in order to preserve some usefulness from previously failed treatments in MDR patients. The problem with this, however, is that the existing mutations represent a lowering of the mutational barrier. The only way to overcome this in the long-term seems to be an increase in the number of drug components used, which may succeed at the goal of reducing viral load at the cost of raising the side effects of the HAART drugs to an unacceptable level. A notable exception to this was the recent Tetriz study The development of drug resistance in HIV infection is driven by two phenomenon: mutation and selection. Mutation in HIV replication occurs at a well-characterized, relatively constant rate of approximately When antiviral medication is used, the wild-type is no longer the fittest virus; their interference with the virus' ability to replicate is such that the virus population will shrink exponentially. Various mutations exist that, if present, reduce the ability of the antiviral drugs to interfere with HIV replication; if they interfere to the extent that the mutant virus population is able to grow overall, the mutation can provide clinically significant resistance.The likelihood of a particular resistance mutation emerging is influenced by two major factors. The first is the relative fitness of the mutation under the current treatment. This may be calculated by considering the relative effectiveness of the mutation at negating the effect of the drug and the relative fitness cost of the mutation. Fitness cost, in this sense, means the decrease in the viruses' ability to effectively replicate in the absence of treatment as a result of the mutation.The second factor influencing likelihood of emergence is the genetic distance of the resistance mutation from the existing virus pool. This is the number of point mutations necessary to generate the resistance mutation. If the HIV genome is considered to reside in a sequence space, the genetic distance is equivalent to the Hamming distance. Because mutation is a random process, mutations with a high genetic distance are very unlikely to emerge.Extensive data on resistance mutations to the antivirals listed above has been collected online at the Stanford HIV database Since the (103N) mutation gives broad class resistance against all NNRTIs, any follow-up therapy will not use NNRTIs. Neither (74V) nor (184V) exhibit strong cross-resistance patterns with any other NRTIs, so a possible follow-up therapy would be the two NRTIs tenofovir and zidovudine together with the PI nelfinavir. Clinically significant resistance to these three drugs could be conferred by the set of mutations  on the viral RT protein and the mutation (30N) on the viral protease protein. This set of mutations has a genetic distance of 4 from the wild-type, but a genetic distance of 6 from the mutant virus generated in the first round of treatment. This is because the inclusion of either the (74V) or the (184V) mutation increases the susceptibility of the virus to both tenofovir and zidovudine. Consequently, any resistant virus arising to the second treatment will probably arise from the wild-type viral pool, and will probably not carry the (74V), (103N), or (184V) mutations.Therefore, after developing resistance sequentially to these two treatment regimens, the patient will be carrying three viral strains; the wild-type, one mutant carrying the  RT mutations and another mutant carrying the  RT mutations and the (30N) Protease mutation,. A resistance mutation to a third antiviral schedule consisting of a permutation of the first two regimens, say abacavir, zidovudine, and nevirapine, would have to arise from one of these parent viruses. The common resistance mutation to this combination with the closest genetic distance to the wild-type carries the mutations  would have a genetic distance of 5. This is also the variant with the shortest genetic distance to the first mutant, with a genetic distance of 4 . The variant with the shortest genetic distance to the second mutant would carry the RT mutations , and would have a genetic distance of either 2 or 3, depending on whether the protease-resistance mutation renders it inviable.The computation of genetic distance between HIV strains is relatively straightforward, but there are a few ways in which the genetic distance can be over- or under-estimated. The first is the non-uniqueness of the genetic code; multiple genomic sequences can code for the same amino acid. The calculations carried out in the previous section assumed the parent genome contained the sequence with the shortest genetic distance to the mutant; this may lead to an underestimation of genetic distance.When using genetic distance to estimate mutational barriers, as described in the next section, the existence of viable transitional forms can result in an overestimation of genetic distance. That is, while the genetic distance to the identified resistant strain may be high, an unidentified partially resistant strain with a lower genetic distance may provide a “stepping-stone” for the development of the fully resistant strain.The research of Bonhoeffer and Ribeiro In this section, equations are presented that determine the drug-resistance emergence risk, which is the mutation probability from the current virus pool to a resistant mutant for the new regimen. To accomplish this, a Poisson distribution is used to model the mutation process. The probability of pre-existing resistant genotypes depends upon two key variables: the total number of active virions for each type of virus present in an infected host, Therefore, assuming a point mutation rate of Consider the simplest case. Assuming that the current virus pool consists of only one kind of virus strain and the genetic distance from the current virus strain to the resistant mutant is either 1, 2 or 3. As To model HIV dynamics, a set of ordinary differential equations is used that includes terms describing the mutations among different virus types. This model depicts the interactions between a wild-type virus population sensitive to all antiviral drug regimens and a resistant mutant virus population only sensitive to treatment with some, if any, antiviral drug combinations. The model is in shown in Equation 2This model includes states CD4+ T cells are generated from their source at rate The infected CD4+ T cells The virus To apply the system of equations describing the evolution of viral loads and CD4+T cells to a specific individual, the parameters of the nonlinear differential equations need to be estimated. Using patient data from the AutoVac study Parameter estimates were generated for each of 12 patients. For each patient, treatment was interrupted and after a period of time, the treatment was restarted. This cycle of interrupting and reinstating the treatment is repeated 3 or 4 times. The MCMC procedure produced 200,000 possible combinations of parameters that are consistent with the patients' data. From this result, the marginal probability densities for of the six parameters can be established. Among the 12 patients, 3 of them have no detectable virus after an interruption and another 3 appear to be subject to multiple large exogenous disturbances  which are not accounted for in our model, and result in poor fits. The results of the other 6 patients by using this identification method are shown in In the case of patients who have failed one or more drug regimens previously, the need to preserve the remaining regimens becomes all the more important. Interestingly, the previously failed regimens provide additional control inputs which can be used to reduce the risk of failure for the new regimen at a lower systemic cost than is possible when only one failing regimen is available to use.The multiple failed regimens allow two options for achieving a transient reduction in viral load. Cycling through the previously failed regimens before returning to the currently failing regimen is one such option. Consider a patient with viral dynamics described by Equation 2 who has developed virus strains Our approach can be formulated as an optimal control problem in two steps. In the first step, the allowable patterns of treatment cycling where either The achievable minimum according to this method will be limited by the initial load levels of the various resistant viruses A better option for inducing a transient minimum in the case of multiple previously failed regimens is to introduce a permuted antiviral regimen. It is very likely that that no strain exists which is resistant to permutations of the previously failed therapies. While an antiviral regimen consisting of the permuted components of previous regimens will not provide sufficient mutational barrier to be a viable long-term option, they will allow a dramatic transient reduction in the total viral load, and the corresponding risk of pre-existent resistance.In the mathematical formulation, the same cost function as Equation 4 is applied. However, the simplified model is not applicable for this case, because In this model, there are multiple virus strains, When utilizing permuted regimens, the optimal switching strategy involves switching from the failing regimen directly to a permutation of previously failed regimens prior to introduction of the naive regimen. Every previously dominant strain will be susceptible to this permuted regimen, so this will result initially in exponential decline in the total viral load. However, the reduced genetic distance inherent in using components of previously failed regimens means that resistance to the permuted regimen is likely to emerge. The expected achievable risk reduction can be estimated by assuming that the strain resistant to the permuted regimen pre-exists, with initial conditions related to measures of genetic distance.Assuming that the two previously dominant resistant strains Although current guidelines Both of these methods use optimization to find schedules that create a transient minimum in the total viral load. Successful implementation of these methods require accurately finding the time when this minimum occurs and switching to a naive regimen at that point. The exact time point of the achieved minimum may vary considerably from its calculated point due to parameter variation and the stochastic uncertainty in calculating initial values of emerging resistant virus The case where a patient has a single previously failed regimen had been the focus of our previous studies Our objective is to find a drug-switching schedule that yields the minimum risk, which is calculated as shown in the method in the Analysis section. For patients with only a single previously failed regimen, this can be achieved only through the use of interrupted schedules of treatment. The concept is identical to that driving the regimen cycling approach described in the previous section, except that periods of no treatment are allowed. If the resistant virus generated during the previous therapy has associated fitness cost with respect to the wild-type virus, then these periods of no treatment allow the wild-type virus to re-establish dominance. Re-introduction of the failing regimen will then result in a transient decrease in total viral load before the resistant strain re-establishes dominance.As in the previous section, this is an optimal control problem in two steps. The optimal schedules consist of an interruption of length An example is used to illustrate how our algorithm works. The simplified model of Equation 2 is employed with the parameters which are identified for Patient 1. Assume that the point genetic distances Treatment interruption regimens have been associated with a high rate of resistance emergence We have presented methods to reduce the risk of drug resistance emergence in HIV by manipulating the viral load prior to introduction of a naive antiviral regimen. These methods rely on creating a transient reduction in total viral load prior to introduction of a naive regimen. If the patient has failed multiple previous regimens, this may be accomplished either through regimen cycling or the use of a permuted antiviral regimen. If the patient has failed only a single previous regimen, this may be accomplished through the use of interrupted therapy. The optimal switching regimens are computed using simple model-based open-loop optimal control algorithms. In all cases, the models predict achievable order-of-magnitude reduction in the risk of resistance to the naive regimen pre-existing its introduction.The method proposed in this paper uses predictive models of HIV evolution under conditions of dynamic treatment to find treatment schedules that minimize the probability of certain resistant strains emerging. The application of dynamical systems and control to evolutionary systems will likely find broader application, as problems of drug resistance continue to increase in other areas of medicine.While risk reduction should be achievable through any of these three methods, regimen cycling and interrupted therapy carry an increased risk of disease progression and/or further development of resistant virus. For these reasons, initial clinical investigations will focus primarily on the method of permuted regimens. Nevertheless, the other two methods may be useful in certain circumstances.The problem of multi-drug resistance in HIV is extremely widespread, and methods that preserve remaining suppressive antiviral regimens have the potential to significant decrease morbidity and mortality in the HIV-positive population. The necessary next steps for implementing this method are outlined below:The methods introduced in this paper have the potential to significantly reduce the incidence of pre-existence related treatment failure. The methods involving permuted regimens could be applied to select groups of patients without significant further work. These patients would have to be in a closely monitored clinical situation, have a history of consistent viral genotyping showing strain patterns amenable to this method, and would have to be available for frequent viral load sampling. For these methods to be more broadly applied, several issues involving measurement, viral load history, and sampling frequency will need to be addressed.The model of Equation 2 represents a highly reduced form of the HIV dynamics, and neglects many known factors in HIV infection. Perhaps chief among these is the immune response to HIV, which can change the infection rate The methods described in this paper rely heavily on the frequent and accurate measurement of the HIV viral load, both for risk computation and model identification. Viral load measurements are complicated by the existence of a detection limit of 50 copies/mL. Targeting viral load reduction below the limit of detection is therefore problematic. However, reduction of viral load to this limit of detection is sufficient in most cases to achieve a significant order-of-magnitude reduction in risk.A second issue related to measurement is the proportion of the measured viral load which is noninfectious. Cells with defective integrated viral genomes may produce replication-incompetent virus particles, and a proportion of the particles produced by all infected cells will also be replication-incompetent. The most direct measurement of this phenomenon estimates that between 5–13% of the total free virus particles are capable of successfully completing the infection process  A third issue, related to the second, is the fact that plasma viral concentrations are not the same as the virus concentrations in the lymphoid tissues, where the majority of the HIV virus resides and the where the majority of virus dynamics occur. HIV virus penetrates into many different tissues in the body, and there is evidence that these tissues are sufficiently compartmentalized to allow for divergent evolution of the virus in different compartments The most promising method presented in this paper is the introduction of permuted antiviral regimens prior to the introduction of a naive regimen. In order to safely choose these permuted regimens, it is necessary to know which resistant viruses are present in the patient's viral reservoirs. Consistent viral genotyping following every treatment failure would provide this information; unfortunately, this is rare. It may be possible to estimate the likely distribution of resistant viruses in a patient based on a history of antiviral use and failure, using genetic distance and fitness information from the HIV database.All the methods presented in this paper induce a transient crash in the viral load, and depend on being able to switch therapies at or near the minimum of this crash, prior to rebound. In this paper, the method suggested for this is consistent, frequent sampling of the viral load during the transient period. While this should work, it is expensive both in economic terms and in terms of patient burden. Optimal minimal sampling methods to find the viral load minima with the fewest possible measurements should solve this issue; this research is ongoing


S. cerevisiae interactome. Complex prediction rates are improved by up to 39%, depending on the clustering algorithm applied.Recent technological advances applied to biology such as yeast-two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of protein interaction networks. These interaction networks represent a rich, yet noisy, source of data that could be used to extract meaningful information, such as protein complexes. Several interaction network weighting schemes have been proposed so far in the literature in order to eliminate the noise inherent in interactome data. In this paper, we propose a novel weighting scheme and apply it to the We adopt a two step procedure. During the first step, by applying both novel and well established protein-protein interaction (PPI) weighting methods, weights are introduced to the original interactome graph based on the confidence level that a given interaction is a true-positive one. The second step applies clustering using established algorithms in the field of graph theory, as well as two variations of Spectral clustering. The clustered interactome networks are also cross-validated against the confirmed protein complexes present in the MIPS database.The results of our experimental work demonstrate that interactome graph weighting methods clearly improve the clustering results of several clustering algorithms. Moreover, our proposed weighting scheme outperforms other approaches of PPI graph weighting. Computational methods that successfully predict protein complexes are of instrumental importance to our understanding of the functions that take place in a living cell. Moreover, these methods can be used to guide biological experiments in order to confirm predicted complexes, therefore resulting in a reduction in the cost of such experiments. Protein complexes in a living cell are of dynamic nature; their composition and cardinality vary according to cell state and the challenges set forth to the cell by its environment. Since the data provided by interaction-detecting experiments lack temporal information, the results provided by clustering the interactome graph depict only a snapshot of the dynamic composition of protein complexes.The problem of clustering protein interaction networks lies in the data itself, since methods that produce high-coverage of the proteome introduce a significant amount of noise in the form of false-positive interactions. On the other hand, methods that produce highly reliable interaction data, suffer from poor coverage of the complete interactome graph. This is known as the problem of noise inherent in protein interaction data, which is a drawback of the methods that detect protein interactions -4.Protein-protein interaction networks are represented as undirected graphs G, in which the nodes V denote the proteins, while the edges E correspond to interactions among them . In the The issue of assigning weights to parameters has long been a crucial issue in optimization and learning from data as this process reflects the importance of single variables or groups of them . On the Modha et al. present an abstract framework for integrating multiple feature spaces in the k-means clustering algorithm . The papSeveral approaches to PPI graph weighting make use of graph-theoretic methods (such as the Czekanowski-Dice distance ). HoweveIn this manuscript, we present a novel noise reduction method by weighting protein interactions assigning higher score to the most probable true ones and a lower score to the ones derived as artifacts of the used detection method. Experiments were carried out using the yeast subset of the iRefIndex database  and resuThe yeast subset of the iRefIndex database  is the dThe majority of the clustering procedures consist of two steps: First, each binary protein interaction is assigned a weight, reflecting the confidence that this interaction is a true positive interaction. Then, the results are clustered using several different clustering algorithms. We performed experiments using all possible combinations of four different weighting schemes (described below) and four clustering algorithms.et al. propose the PRODISTIN method of functional clustering of proteins based on the principle that the higher the number of common interactors shared by two proteins, the more likely they are to be functionally related [st degree and 2nd degree neighbors is calculated using the Czekanowski-Dice distance (CD-distance). More recently, Liu et al. proposed the Adjust-CD [Brun  related . In theidjust-CD  weightindjust-CD  and consLubovac et al. introduce two PPI graph weighing schemes ,22 that et al. [et al., interactions detected by different experimental methods provide a set of interactions that is more accurate, even if the coverage of the interactome is rather limited.Von Mering et al.  recognizet al. . Accordiet al. calculate the reliability of an experimental source by computing the fraction of interacting proteins that share the same function [et al. assigns to each interaction a weight that is calculated as a function of the reliability of the experiment that reports the interaction.Similarly, Nabieva function . The weiet al. separate experimental methods in 3 categories: in vivo, in vitro and yeast-two-hybrid methods. Subsequently, they assign weights to interactions according to the combination of experimental categories by which the interaction was detected [In a more recent contribution, Pinkert detected .et al. also apply a weighting scheme, which does not distinguish between high- or low-throughput experiments, but boosts interactions that are detected in different experimental methods [Pereira - Leal  methods .et al. [Using information derived from the work of von Mering et al. , we defiBelow we present two PPI graph weighting schemes that use the concept of experiment plurality, which is defined as the number of protein interactions reported by an interaction detection experiment. The first one is a novel weighting scheme, called MV scoring, and it is the main contribution of the present manuscript. The second one, called Simple Scoring, is based on the basic assumption that most scoring schemes use and it is used purely for evaluation purposes.Ne) that report an interaction  takes into account the statistical distribution of the number of experiments , the interaction will be assigned a high confidence score using the above formula (Equation 1).α affects only interactions reported by more than one experiment (Ne > 1). A higher value of α conveys higher confidence levels to such interactions, whereas a smaller value tends to give the relative advantage to interactions that are reported by one experiment, with smaller plurality number. The value producing the best results has been experimentally adjusted to α = 2.The user-assigned factor Purely for evaluation purposes, we define a naïve weighting scheme, which assigns a weight to an interaction based on the number of experiments (Ne) reporting the interaction, and the plurality of each one of those experiments. Based on the fact that high-throughput experiments are prone to detect false-positive interactions -4, if thA number of algorithms have been proposed for clustering protein interaction networks. In order to cluster the weighed PPI graph, we only used the algorithms that support weighted graphs, such as MCL , the CMCThe RNSC algorithm  searchesThe COACH algorithm  first deThe Markov Clustering algorithm (MCL)  finds clet al., propose and use the Adjust-CD [More recently Liu, Wong, and Chua proposed the Clustering on Maximal Cliques algorithm (CMC) . CMC firdjust-CD  weightinet al. spectral graph decomposition [Additional experiments were carried out by using two variations of a Spectral Clustering algorithm. Using the Ng position , we map position .Following the spectral decomposition, we apply to the set of resulting points two clustering algorithms, the recently proposed Kmeans++ algorithm  and the et al. [et al. extract such information using the eigenvalues of the decomposed graph and then sort the quasi-cliques according to their interconnectivity.Using a different approach, Bu et al.  proposedA more detailed report of the clustering algorithms used in PPI clustering is beyond the scope of this paper. A recent evaluation of clustering methods is given in .Eliminating the noise inherent in the data is of vital importance in order to produce a valid clustering result. This is especially true in the PPI clustering context, since interactome data feature much noise mainly in the form of false positive interactions. The results presented in Figures In order to compare the clustering results, we validate them against the list of known complexes present in the MIPS database . The ideet al. [Positive Predictive Value, Sensitivity and Accuracy. We also use a prediction rate metric which is defined as the percentage of predicted clusters that match known complexes [The metrics used to compare the algorithms' performances are mainly derived from the work of Brohee et al. , namely omplexes .As far as the complex prediction rate is concerned, all tested algorithms benefit from the application of the MV weighting scheme  rating for a clustering algorithm would mean that the algorithm predicts protein complexes in which every protein belongs to the matching confirmed complex. High PPV value  cannot go without a loss of recall (sensitivity). This is evident when comparing the PPV and sensitivity rating of the CMC algorithm (see Figure The price for this, however, is that the detected clusters lack several proteins that their corresponding reference set complexes feature. This holds also true for the results of Spectral methods when using the Adjust-CD weighting and the combination of the EM algorithm and the ETW weighting. Moreover, in contrast to all other tested algorithms, the sensitivity rating of the MCL algorithm was not hindered by the use of the Adjust-CD weighting scheme.The Accuracy results chart Figure  summarizSpectral methods feature the best results for the unweighted graph compared to other clustering algorithms, although their out-performance compared to the MCL algorithm is decreased when using weighted graphs. This is largely due to the beneficial effect of graph weighting to both the PPV and sensitivity performance of the MCL algorithm. Furthermore, the combination of spectral methods and Adjust-CD weighting is the only one that features worse results compared to the unweighted case. This is expected, taking into account the poor sensitivity performance of this combination of algorithms and weighting scheme (see Figure In Figure A stronger effect of interactome graph weighing is shown in Figure In Figure Summarizing, the combination of the MCL algorithm and the Adjust-CD features the best prediction rate and the second best sensitivity results. On the other hand, the combination of the Spectral-Kmeans++ algorithm with the MV weighting scheme features the best PPV and accuracy results. Taking all the above information into account, it becomes obvious that the best performing weighting schemes are the MV and the Adjust-CD ones. However, since the Adjust-CD one hinters the results of the spectral methods, we favor the use of the MV weighting scheme.Finally, we note that a direct comparison between the CMC and the other clustering algorithms tested is not feasible, because the CMC algorithm, in contrast to MCL, Spectral-Kmeans++ and Spectral-EM algorithms, can assign a protein to more than one clusters. Arguably, this is a desirable property of a PPI clustering algorithm. However, applying the CMC algorithm to the current input data using the default parameters produced an exceptionally large number of clusters, which accounts for the lower performance compared to other algorithms.In this paper, we applied four different methods to introduce weights to the edges of the interactome graph according to the likelihood that an edge corresponds to a true positive interaction and conducted experiments using four different clustering algorithms.The main contribution of this work is the development of a new weighting scheme, called MV scoring, which features superior noise reduction properties compared to known PPI weighting schemes.As an outlook, we plan to further investigate the application of soft cluster assignment algorithms in protein interaction networks and assess the biological significance of our results.The authors declare that they have no competing interests.GK conceived the study, performed the experiments and wrote the paper. CM helped conducting the clustering experiments and aided revising the manuscript. MV conceived the MV weighting scheme and provided expert view on the clustering algorithms used and experiments conducted. SK guided the study and assisted in writing the manuscript. All authors read and approved the final manuscript.


Muscular force generation in response to external stimuli is the result of thermally fluctuating, cyclical interactions between myosin and actin, which together form the actomyosin complex. Normally, these fluctuations are modelled using transition rate functions that are based on muscle fiber behaviour, in a phenomenological fashion. However, such a basis reduces the predictive power of these models. As an alternative, we propose a model which uses direct single molecule observations of actomyosin fluctuations reported in the literature. We precisely estimate the actomyosin potential bias and use diffusion theory to obtain a Brownian ratchet model that reproduces the complete cross-bridge cycle. The model is validated by simulating several macroscopic experimental conditions, while its interpretation is compatible with two different force-generating scenarios. Forty years ago, A.F. Huxley and R.M. Simmons ad-hoc dependencies on the chemical reaction coordinate or base the transitions on hidden assumptions of the actomyosin potential energy. In other words, actomyosin properties are deduced by fitting the macroscopic behaviour of the muscle fiber even though the goal of the model is to interpret the muscle behaviour from the actomyosin properties. We believe that this approach reduces the predictive power of such models because the oscillatory behaviour of the actomyosin complex is a fundamental property of muscle function such that its description cannot be restricted to phenomenological rate functions. Therefore, we here describe an alternate model based on diffusion that considers the entire Lymn-Taylor cycle  state have been observed experimentally by attaching a single myosin II molecule to a large micro-needle and associating it with an actin bundle In both scenarios, the steps are generated by stable actomyosin states which mathematically correspond to several minima in the potential energy, eraction , right. To model the macroscopic response  simulation of the muscle system. The reason is that for equation (1) to have any statistical meaning, the time step of the simulation must be at least two orders of magnitude less than the characteristic time scale of the system. We therefore introduced the following constraints. We set Numerically, we imposed and  see . Thus, wmentally , findingSummarizing, the protein drag coefficient, A comparison with other macroscopic models is difficult to make due to differences in fundamental conditions and to the wide range of simulated data. Despite that, the number of free parameters is relatively low and mostly attributed to the attachment-detachment process.We quantitatively tested our model for two classical skeletal muscle experiments: fast tension recovery after a small increment in isometric length (length clamp), and velocity of contraction against a constant load (load clamp). For the first case, a fast (microsecond) and small  change in muscle length, ehaviour , inset. c manner  [36].The model can simulate the length clamp behaviour by using equation (1) and assuming:Simulations for both   curves  and the .  curve  show verTo further investigate the model predictions, we simulated the number of attached myosins during isokinetic contraction under different external loads and compared the results with experimental data obtained from pothesis , lower. pothesis , upper. Finally, we can conclude our model results are not due to inefficient cycling . Noting that each detachment process consumes one ATP molecule, we measured the efficiency of the flashing Brownian ratchet as the product of the force and the velocity of contraction divided by the total energy consumed In this work, we have used diffusion theory to model muscle mechanics, defining some parameters using SME data and quantitatively simulating several macroscopic behaviours. The model satisfies two different hypotheses regarding the origin of the actomyosin stable states, which are often viewed as stable states of the lever arm (scenario 1). This interpretation gives a clear picture of the role of the lever arm structure in muscle contraction and is compatible with X-ray reflections during isotonic contractions that describe the regular arrangement of myosin motors on the backbone It is worth noting that scenario 1 allows for more flexibility than scenario 2 when defining parameters such as the distance between minima. Nevertheless, the good fitting obtained shows that either scenario is consistent with the experimental data. Moreover, high speed AFM showed that a myosin V head undergoes brief translocation along actin by repeatedly detaching and attaching after Pi release, i.e., at the force generating state One limit of our model is that the contraction velocity is slightly underestimated for mean values of applied force. Consequently there is an enhanced underestimation of the maximum power output  . This liAlthough the mechanics of muscle contraction have been well studied, a comprehensive model that reproduces at the same time all macroscopic behaviour is still lacking. Furthermore, one weakness in muscle modelling is that the same behaviour can be reproduced starting from different working models. We believe that this is in part because the description of the oscillatory behaviour of the actomyosin complex, which is generally accepted as a fundamental property of muscle function To emphasize the importance of this oscillatory behaviour, we have applied a new approach to muscle modelling, where actomyosin complex dynamics are described by the diffusion of particles constrained within a defined energetic landscape that is described by SME data. Having inferred the bias of actomyosin energy, we showed the feasibility of this approach for quantitatively describing several macroscopic behaviours. Furthermore, the new approach reduces the number of free parameters and makes them constant rather than empirical functions that are based on chemical reaction coordinates. This model can potentially be a basis for future developments where parameters that describe the behaviour of single molecules can be built upon to understand all contraction mechanism details, such as how molecular cooperation leads to macroscopic behavior.Figure S1SME set-up from . An external system (microneedle) with a very high drag coefficient is linked to a multistable particle . The motion of the particle is analysed through the position of the microneedle. A linear spring with symmetric stiffness links the two bodies.(EPS)Click here for additional data file.Figure S2Example of a simulated microneedle trace based on  The myosin head is always in the attached configuration. The trace is comparable with the experimental results obtained in (EPS)Click here for additional data file.Figure S3Simulation of the isometric contraction. The simulated rising phase is slowed by a factor of (EPS)Click here for additional data file.Figure S4Distribution of the attached myosin heads (insets) in the four minima of actomyosin energy  during different phases of the unloaded force-clamp simulation (continuous line). Scale in the insets is normalized to the number of attached heads.(EPS)Click here for additional data file.Figure S5Power output predicted by the model (blue triangles) and comparison with experimental data (black circles). The lower velocity of contraction at intermediate tensions leads to an underestimation of the maximum power output. This drawback is common with other models and is related to the attachment-detachment process (see main text). Mean values(EPS)Click here for additional data file.Text S1(PDF)Click here for additional data file.