New democracies go to great lengths to implement institutional protections of the electoral process. However, in this paper we present evidence that shows that even in the United States—where the secret ballot has been in place for generations—doubts about the secrecy of the voting process are surprisingly prevalent. Many say that their cast ballot can be matched to their name or that others could observe their vote choices while they were voting. We find that people who have not previously voted are particularly likely to harbor doubts about the secrecy of voters’ ballots. Those who vote by mail in the privacy of their own homes also feel that others are able to discover their vote choices. Taken together, these findings suggest an important divergence between public perceptions about and the institutional status of the secret ballot in the United States, a divergence that may affect patterns of voting behavior and political participation. Democracies are often defined by the rules and procedures that govern their elections. Great effort is put forth to create a system of laws and procedures that promote “fair elections” where the outcome is likely to be widely viewed as legitimate and losing factions accept defeat in peace. Many of these rules and procedures are designed so that all citizens can make choices on their ballots as they see fit and participate in the political process without fear of harassment from employers, neighbors, and elected officials. However, formal rules and institutions may only have their intended effect if people understand how they are structured and believe that they work.We investigate whether perceptions of the operation of a key democratic institution, the secret ballot, deviate from the legal and practical reality of that institution. Such deviations may be consequential. Lack of information (or misinformation) about the secrecy of the voting process may affect who votes and, perhaps, which candidates voters support on Election Day –3. More Prior work finds that many people report general doubts about the secrecy of the voting process and that these doubts may have repercussions for voting behavior . For exaexperienced as private. We make two contributions to understanding of public perceptions about the secrecy of the voting process.We conducted a national survey to gather fine-grained measures of citizens’ experiences and perceptions about aspects of the voting process that might lead to doubts about ballot secrecy. The survey allows us to shed light on exactly how people think their vote choice might be discovered by others. We consider elements of the voting process tied to the operation of formal institutions , as well as less formal, social aspects of the process . Improving our understanding of the contours of doubts about ballot secrecy is likely to be important to practitioners who wish to develop more effective interventions to ensure that the act of voting is First, we present detailed evidence about the prevalence of doubts about ballot secrecy, as well as about perceptions about how secrecy may be compromised by election officials or other voters—perceptions that may lead people to view voting as a public, rather than private act. We find that although most citizens in the contemporary United States believe their voting choices are secret, a substantial number of citizens harbor doubts or misunderstandings about the voting process. Many believe that their ballot includes personally identifying information, that elected officials can access records of their vote choices, or that other voters at the polling place will observe or ask about their choices.Second, we assess whether these perceptions vary with key features of individuals’ voting experiences. We examine differences between those who cast paper versus electronic ballots and between early voters and those who voted on Election Day. Although these may be different populations , these comparisons suggest that those who cast paper ballots in-person on Election Day harbor fewer doubts about ballot secrecy than those who cast electronic or early ballots. However, with some notable exceptions, the magnitudes of the differences we find are modest. We do find evidence that those who vote by mail report experiences and perceptions that are inconsistent with the notion that voting is a private act. We also compare the perceptions of respondents who reported voting in the last general federal election to those who said they either had never voted or had voted, but skipped the last election. These comparisons reveal substantial differences. Those who indicated that they did not participate in the previous election are less certain about the secrecy of the process, and those who say they have never voted are even more likely to harbor doubts. For example, compared to those who have voted, non-voters are much less likely to say that voters do not write their name on their ballot.In the next section of the paper we briefly outline prior work on the importance of the secret ballot and citizen beliefs about its proper implementation. We also briefly lay out reasons to expect these perceptions to vary with voting technology and timing (early v. Election Day), as well as with how recently one has voted—or whether one has ever voted. We then describe our data source, the basic characteristics of our sample, and respondents’ general beliefs about the secrecy of their vote choices. Next, we describe the voting experiences and perceptions of respondents who reported casting an in-person paper or electronic ballot—either early or on Election Day—the last time they voted. Then, we assess how these perceptions vary with voting technology , timing of voting (early versus on Election Day), and between recent voters and those who have either not voted recently or have never voted.The secret ballot is one of a set of democratic institutions—e.g., freedom of speech, freedom of association , universal suffrage, and due process of law—designed to foster competitive and legitimate democratic elections. The ability to vote without one’s choices being revealed to others is considered an essential characteristic of legitimate democratic systems . The secOther work suggests that perceptions about ballot secrecy are likely to be consequential. Individuals’ experiences at the polling place, including their sense of privacy while voting, can affect both evaluations of poll workers and confidence in the electoral process as a whole . In a fiTwo aspects of the process of casting a ballot may be particularly important for understanding people’s voting experiences and the sources of doubts about the secrecy of one’s ballot. First, the official formal aspects of the voting process, including interactions with election administrators and perceptions about whether voting procedures protect the anonymity of their ballots, may play an important role in whether people think of voting as a private or public act. Although voting in the United States is conducted by secret ballot and is explicitly designed to ensure the privacy of people’s choices on Election Day, many people may be unfamiliar with the rules and regulations election administrators must adhere to and may therefore think that their vote choices are a matter of public record. Alternatively, people may not be confident that these procedures work.Second, the social aspects of the voting process may affect how people think about voting. These social aspects include people’s assessments of whether their polling place provides an environment where they can cast their ballots privately, as well as whether people go to the polls alone or with other voters and whether they discuss their choices with others. Even if people recognize formal ballot secrecy protections and trust election officials, they may nonetheless view voting as a public act. For example, they may assume that other voters can see their ballots while they are filling them out or that other voters will ask them to discuss their choices at the polling place.Beyond offering new evidence regarding aggregate perceptions about ballot secrecy, we consider several key aspects of citizens’ voting experience that may be tied to perceptions about ballot secrecy. First, we compare the perceptions of in-person voters who cast paper ballots to those who cast electronic ballots. Although ballots recorded electronically are, in theory, no different in terms of the level of anonymity they provide, existing work suggests that people harbor doubts about electronic voting –12. SpecSecond, we consider whether secrecy perceptions vary depending on when and where individuals cast their ballots. We compare the perceptions and experiences of those who voted in-person on Election Day to those who cast early, in-person ballots. We posit that those who vote early are less likely to face long lines and busy polling places and, on average, may therefore feel that their ballot is easier to identify because it is not being immediately pooled with as many other ballots. It is also possible that early voters harbor a misperception that election officials need to be able to personally identify their early ballot to ensure that they do not vote more than once.We also assess whether those who reported voting by mail diverge in their perceptions about the secrecy of their ballots. As with electronic voting, existing work finds that those who cast mail ballots are less confident that their votes will be counted properly  and may Finally, we compare the secrecy perceptions of those who reported voting in the federal election prior to our survey to those for whom the experience of voting may be more remote. In particular we compare the reported experiences and perceptions of these individuals to those reported by individuals who said they had voted before but did not vote in the most recent election. We also compare the beliefs of recent voters to the secrecy expectations reported by individuals who said they had never voted before. Again, there is reason to expect differences across these groups. Casting a secret ballot is an unusual act compared to most other forms of human interaction. Typically, when we are called upon to make a choice we are expected to disclose our preferences directly. Thus, memories of one’s last voting experience may become murky quite rapidly. In contrast to those who cast a ballot a month prior (our survey was fielded about a month after the election), those who have not voted in two years may fail to recollect important details about the voting experiences and report greater doubts about the privacy the process affords. Similarly, those who have never experienced voting may harbor even greater doubts because they have not directly experienced the voting process.https://doi.org/10.7910/DVN/ZDSD9S.To investigate these questions, we fielded a survey in December of 2010 through YouGov/Polimetrix, which uses a combination of sampling and matching techniques to approximate a random digit dialing sample. The Yale University Institutional Review Board approved this study as exempt. Section A of the Our core survey questions focused on respondents’ experiences in the election in which they had most recently voted. We exclude 124 respondents  from the analysis we present below. These respondents include those who: did not indicate when they last voted (N = 4); reported voting but did not recall when or how they cast their ballot (N = 17); and reported having voted in-person on Election Day, but either cast “lever” ballots (N = 72) or an unidentified technology (N = 31). Thus, our full sample consists of 2,876 observations. We present the unweighted descriptive characteristics of our sample in Table S1 of the Supplementary information document.Approximately 82 percent of respondents in our sample reported voting in the 2010 general election, five percent reported last voting between the 2008 and 2010 general election, six percent said they last voted in the 2008 general election, and three percent said the last time they voted was prior to the 2008 election. One hundred and twenty-one (unweighted) respondents—4.6 percent of the weighted sample—reported never having voted. The reported rate of turnout—82 percent—is high, perhaps because participants in opt-in surveys tend to be more interested or informed than an average citizen . We wereConsistent with previous research that has examined whether people harbor doubts about the basic secrecy of the voting process, we find that a substantial proportion of respondents express concerns about the secrecy of their vote choices. We asked, “When you cast a ballot, are your candidate and other vote choices kept secret unless you tell someone, or might your ballot be revealed to others or matched to your name without your permission?” Approximately 12 percent of the weighted sample said their choices were not kept secret. A second question asked how easy respondents thought it would be for others to discover their choices, regardless of whether they believed their choices were generally kept secret. Specifically, we asked, “According to the law, which candidate you vote for is supposed to be kept secret unless you tell someone. Even so, how difficult do you think it would be for politicians, union officials, or the people you work for to find out who you voted for, even if you told no one?” Thirty-six percent of respondents reported that it would be either “not difficult at all” (12 percent) or “not too difficult” (24 percent). Note that seven respondents did not provide responses to each of these items, thus N = 2,869. This compares to 37 percent, 40 percent, and 41 percent in opinion surveys fielded in 2005, 2008, and 2010, respectively [Among respondents who reported having voted before, 67 percent said that the last time they voted they did so in person on Election Day and an additional 14 percent reported voting early in person. Nineteen percent reported voting via mail or absentee ballot —a distribution that is consistent with previous surveys . We askeWe asked a random subset of respondents (N = 889) whether they thought elected officials can access their voting records to figure out who they had voted for and found that 36 percent of in-person voters answered “Yes.” In short, a substantial share of voters cast ballots that they believe can be accessed by officials. We present responses to the remaining three questions about formal threats to ballot secrecy, as well as the four questions about disclosure to other voters in As the figure shows, for beliefs about the anonymity of their physical ballots, a non-trivial proportion of respondents reported either writing their name on their ballot (six percent) or that there was some information on their ballot that could be used to identify the ballot as theirs (11 percent). Respondents who said that their ballot contained personally identifying information were asked what that information was in an open-ended follow-up question. Fifty percent said that their ballot listed an identifying code , 30 percent said their name or information about their address was listed. Approximately 12 percent indicated that they did not know what the identifying information was and the remaining eight percent provided responses that were too vague to code . Additionally, over seven percent of respondents said they did not remember whether they had written their name on their ballot and 13 percent said they did not remember if their ballot included identifying information. In other words, our findings indicate that, for example, nearly 25 percent of in-person voters did not affirm that the ballot they cast was devoid of personally identifying information. The final question asked whether a poll worked looked at the respondent’s ballot. Only three percent of in-person voters said that a poll worker looked at their ballot and saw who they were voting for, with an additional five percent saying they did not remember.The bottom four items asked in-person voters about whether their choices might have been revealed to other voters during the process of voting. Only three percent said someone at the polling place asked them who they were voting for and only five percent said that they were able to see who another voter was voting for. However, 22 percent said there was no curtain or privacy screen around their voting space and over 20 percent said that someone walking by could see who they were voting for.Note that the values reported in the figure, along with sample sizes for each item  are presented in tabular form in the Taken together, the findings reported in Next, we assess how secrecy perceptions vary with key features of respondents’ voting experiences. We use OLS regression models to estimate whether secrecy perceptions were tied to voting method and timing , or whether the voter had cast a ballot recently (or ever). In each case we set the outcome value to 100 for those who expressed doubts about secrecy (including those who said “don’t know/remember”) and to zero for those who expressed no doubt. We regress each item on indicators for: 1) those who cast electronic ballots the last time they voted ; 2) early voters and 3) those who voted by mail (each set to zero for non-voters); 4) those who reported having voted but not in the 2010 general election, and 5) those who never voted. Then we estimate a second model controlling for core respondent demographics  to account for the possibility that any differences of interest may be attributable to a correlation between, say, the decision to vote early and these characteristics .We find far more pronounced differences tied to how recently respondents’ voted. For example, those who reported having last voted prior to the previous federal election were about 20 percentage points more likely than those who voted in the last election to say they wrote their name on their ballot (or couldn’t remember whether they did). The corresponding difference for recalling whether their ballot included a personal identifier was 15 percentage points. These voters were also notably more likely to say a poll worker had looked at their completed ballot. Those who had never voted expressed even less confidence that their ballots were anonymous and that poll workers would not look at their choices. These individuals were 35 to 40 percentage points more likely to express doubts about these matters.Finally, in We do find evidence that those who had voted before but sat out the prior election were more likely to voice doubts about this type of secrecy. Specifically, they were more likely than recent voters to say someone in line asked who they were going to vote for (or that they could not remember). They were also less likely to affirm that they could not see other voters’ ballots. As with the findings reported in Figs We did not ask those who reported voting by mail the same questions as we asked in-person voters. However, there is reason to suspect that the experience of voting is a social one for those who cast votes by mail. For example, we asked these voters whether anyone else was in the room with them when they cast their ballot and over 23 percent of respondents said that at least one other person was in the room with them when they filled out their ballot. We asked those who reported that at least one other person was in the room with them when they filled out their absentee/mail ballot a series of additional questions about their experiences to determine the extent to which casting mail and absentee ballots is a social rather than private experience. Of these respondents, 85 percent said that one person was in the room with them and 14 percent said two or three people were in the room with them. Additionally, 17.2 percent of all respondents who voted by mail said that at least one other person in the room with them while they filled out their ballot was also filling out a ballot, 17.8 percent said they discussed who they were voting for with someone else in the room, and 8.5 percent said they asked someone else for advice about how to vote on a particular race or issue while filling out their ballot. More than six percent of our mail voters reported showing their ballot to someone else after filling it out. In short, for some people the process of casting a mail or absentee ballot is a social act where they reveal their choices to others.The secret ballot is an important feature of legitimate democratic states. For a voting process to generate legitimacy, however, citizens must be aware of the institutions that are set up to protect the secrecy of the ballot and believe that these institutions are implemented honestly and effectively. The data presented in this paper, however, call into question the assumption that the adoption of formal rules for ballot secrecy in the contemporary United States has fully addressed concerns about the legitimacy and sanctity of the voting process.For example, many people believe that elected officials can and do access information about who a citizen voted for. Additionally, respondents believe the operation of polling places is insufficient to protect the privacy of choices from election administrators or other citizens. For some of the items we asked in-person voters, as many as 35 percent express explicit doubts about the rules and practices that should be in place to protect ballot secrecy or report experiences that suggest that those protections do not work effectively. While the average respondent believes their ballot is secret, the evidence we present implies that many Americans have at least some doubts about the integrity of the voting process. Even for experienced voters, these doubts may discourage them from coming to the polls or supporting their preferred candidate in some contests.Additionally, these concerns about ballot secrecy are substantially more common among those who have never previously voted. For example, half of those who had not previously voted think elected officials access voting records and nearly 60 percent either think that there would be personally identifying information on their ballot or do not know. These doubts among those who have not voted before raise a troubling concern: might some citizens decide to stay away from the polls because they anticipate that their choices may be revealed and expose them to unwanted social pressures or sanctions?At the same time, our evidence also raises doubts about whether changes in voting practices are the best way to remedy these doubts. We find only modest differences between early and Election Day voters and between those casting electronic, rather than paper ballots. Nor does voting by mail, which allows voters to remove themselves from the physical and social interactions at the polling place that might be seen as most obviously threatening ballot secrecy, seem to be a panacea.Most by-mail voters do not fill out their mail ballots in private and many openly discuss their choices with others at the time that they make their choices. While when a by-mail voter fills out her ballot is under more control than for those who must vote in a polling place, sizeable proportions of those casting ballots by mail report that elected officials can access their voting records after the fact (42 percent). For this reason, it does not appear that errors in the implementation of polling place elections are the sole source of doubts about the integrity of the voting process. Doubts about the institution of the secret ballot may not be resolved with better implementation at the polling place, nor with a move to all-mail elections.Instead, our results suggest widespread misperceptions about the voting process and ballot secrecy, rather than failures of implementation. Existing research shows that providing information about the voting process from a Secretary of State's office increases turnout . The surThere are of course some important caveats associated with the results here. First, our analysis is based on self-reports of perceptions and doubts. The behavioral reality and validity of these reports are of crucial importance to the policy implications of our findings, and merit future work on behavioral consequences. The self-reported behaviors and perceptions we rely on may be contaminated by social desirability biases. Reassuringly, the patterns we identify do not change substantially when we use validated rather than self-reported measures of turnout. We have also attempted to characterize the sources of misperceptions and doubts from these survey data, but these are only valid to the extent we have properly accounted for confounding factors and the possibility of reverse causality. For example, one possibility is that individuals who are not disposed to participate offer pessimistic responses to questions about ballot secrecy as a way of justifying their decision to abstain. Future research could consider panel analysis in consideration of this question, however there is also field experimental evidence that messages designed to allay concerns about ballot secrecy increase turnout among those who have previously not voted . This suS1 Appendix(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.


Fritillaria species. Additionally, the effective chemical constituents are identified by HPLC combined with a chemical identification method to classify Fritillaria. The HPLC fingerprint data and HCA  show that Fritillariae Cirrhosae Bulbus is clearly different from Fritillariae Thunbergii Bulbus and Fritillariae Hupehensis Bulbus, but there is no difference between Fritillariae Cirrhosae Bulbus, Fritillariae Ussuriensis Bulbus, and Fritillariae Pallidiflorae Bulbus. These results show that DNA barcoding and HPLC fingerprinting can discriminate between the five Fritillariae Bulbus types and trace species to identify related species that are genetically similar.Fritillariae Bulbus is a precious Chinese herbal medicine that is grown at high elevation and used to relieve coughs, remove phlegm, and nourish the lungs. Historically, Fritillariae Bulbus has been divided into two odourless crude drugs: Fritillariae Cirrhosae Bulbus and Fritillariae Thunbergii Bulbus. However, now the Chinese Pharmacopoeia has described five Fritillariae Bulbus—the new additions include Fritillariae Pallidiflorae Bulbus, Fritillariae Ussuriensis Bulbus, and Fritillariae Hupehensis Bulbus. Because the morphology of dried Fritillariae Bulbus is similar, it is difficult to accurately identify the different types of Fritillariae Bulbus. In the current study, we develop a method combining DNA barcoding and high-performance liquid chromatography (HPLC) to help distinguish Fritillariae Cirrhosae Bulbus from other Fritillariae Bulbus and guarantee species traceability of the five types of Fritillariae Bulbus. We report on the validation of an integrated analysis method for plant species identification using DNA barcoding that is based on genetic distance, identification efficiency, inter- and intra-specific variation, calculated nearest distance, neighbour-joining tree and barcoding gap. Our results show that the DNA barcoding data successfully identified the five Fritillariae Bulbus by internal transcribed spacer region (ITS) and ITS2, with the ability to distinguish the species origin of these Fritillariae Bulbus. ITS2 can serve as a potentially useful DNA barcode for the  Fritillaria cirrhosae D. Don, Fritillaria unibracteata Hsiao et K. C. Hsia, Fritillaria przezvalskii Maxim, Fritillaria delavayi Franch, Fritillaria taipaiensis P. Y. Li, and Fritillaria unibracteata Hsiao et K. C. Hsia var. wabuensis Z. D. Liu, S. Wang et S. C. Chen [Fritillaria walujewii and Fritillaria pallidiflora Schrenk, which are mainly distributed in the Xinjiang province [Fritillaria ussuriensis Maxim, Fritillaria thunbergii Miq, and Fritillaria hupehensis Hsiao et K. C. Hsia, respectively. Wild Fritillariae Cirrhosae Bulbus, which has excellent quality and good curative effects, is distributed between the altitudes of 3000 and 5000 m in most parts of Tibet, Northwest Sichuan, Northern Yunnan, Southeastern Qinghai, and Eastern Europe [Fritillariae Bulbus (Bei-mu in China) is a well-known traditional Chinese medicine that has been known for more than 2000 years for its ability to moisten the lungs, resolve phlegm, and relieve coughs . Historiprovince . Fritilln Europe . Becausen Europe ,7,8. Then Europe , signifin Europe ,11.In recent years, identification methods for Fritillariae Cirrhosae Bulbus have been developed, including the determination and identification of total alkaloids by near-infrared spectroscopy. Microscopic identification was carried out by observing the characteristics of starch granules and the shape of the umbilical point of starch granules in bulbs. High-performance liquid chromatography (HPLC) was used to identify isosteroidal alkaloids ,13,14. HrbcL, matK, psbA-trnH, and trnL-F to identify plant species and analyse phylogenetic relationships [matK and RPS16 to distinguish five Fritillariae species [Fritillaria resources was similar to that of Fritillariae Cirrhosae Bulbus [There is a foundation for distinguishing the authenticity of various plants and animals by establishing DNA barcodes. Scientist Chen et al. uses DNA sequences as a taxonomic basis to design barcodes ,17,18,19ionships ,26,27,28 species . Wang et species . They coe Bulbus ,32,33,34matK, psbA-trnH, ITS, and ITS2, for their validity as DNA barcodes to identify species in Chinese medicinal Fritillariae Bulbus. To establish a method that enables the species traceability of Fritillariae Bulbus, we performed experiments to quantify four chemical markers using HPLC/ELSD.To control the quality of crude drugs, it is necessary to confirm their identities and ensure the species traceability of Fritillariae Bulbus. In this study, we tested four candidate loci, namely, the chloroplast gene regions psbA-trnH—all showed PCR amplification and high sequencing efficiency (100%). The locus matK showed no PCR amplification and a sequencing efficiency of 0%. Moreover, the effective sequence ratios of ITS, ITS2, and psbA-trnH were the same (100%).The three loci—ITS, ITS2, and The lengths of the aligned sequence (base pairs) and variable sites for the ITS and ITS2 regions were 610/46 and 235/18, respectively. The results are shown in The NJ tree constructed from 44 ITS sequences showed that Fritillariae Cirrhosae Bulbus could be clustered into one group, Fritillariae Thunbergii Bulbus and Fritillariae Hupehensis Bulbus could be clustered into one group, Fritillariae Pallidiflorae Bulbus could be clustered into one group, and Fritillariae Ussuriensis Bulbus could be clustered into one group. The results are shown in Fritillaria cirrhosae was clustered into a group of circle samples with Fritillaria ussuriensis as black marker. The results are shown in Fritillaria. The alkaloid content is shown in Fritillaria were similar. The results were consistent with the results of fingerprint analysis by HPLC. Therefore, HCA can also help to distinguish Fritillaria plants, but it is not enough for identification.To validate the results of the HPLC fingerprint analysis and further elucidate the resemblance relationship among the samples, hierarchical clustering analysis (HCA) was applied using the Statistical Product and Service Solutions (SPSS)19.0 software and the Unscrambler X 10.0 software. HCA results showed that A total of 44 Fritillariae Bulbus medicines were analysed by chromatographic fingerprints and a principal component diagram. All samples were divided into three parts. SPSS 19.0 was used for systematic clustering, and the clustering method of inter-group connection was adopted. The measurement standard was the squared Euclidean distance, and the effective percentage of samples was 100 percent. Chromatographic data showed that Fritillariae Thunbergii Bulbus, Fritillariae Hupehensis Bulbus, Fritillariae Ussuriensis Bulbus, and Fritillariae Pallidiflorae Bulbus had similar fingerprints. The Fritillariae Cirrhosae Bulbus samples were clustered into one branch, and the counterfeit products were clearly on different branches. Fritillariae Cirrhosae Bulbus and Fritillariae Thunbergii Bulbus had similar fingerprints. These results showed that HPLC cannot distinguish the two kinds of traditional Chinese medicines. The results are shown in Fritillaria species have similar morphologies. Wild Fritillariae Bulbus grows in high altitude areas and is difficult to harvest, requiring a large amount of manpower and material resources. It is very important to identify Fritillariae Bulbus effectively. It is difficult to distinguish Fritillariae Cirrhosae Bulbus from other Fritillariae Bulbus medicinal materials with traditional methods. Powder identification is also a common method for the identification of traditional Chinese medicines. Fritillariae Cirrhosae Bulbus and other Fritillariae Bulbus medicinal materials are white, tasteless powders. The classification of Fritillariae Cirrhosae Bulbus medicinal materials has always been controversial, and there are differences among different types of Fritillariae Cirrhosae Bulbus medicinal materials in the Chinese Pharmacopoeia. DNA barcode identification may be useful in the classification of Fritillaria parent sources. The ITS and ITS2 gene regions have been written into the Chinese Pharmacopoeia and have been widely used to identify plants of the Fabaceae and Compositae families as well as other plants that are traditionally used in Chinese medicines. ITS and ITS2 have good amplification efficiency for the identification of Fritillariae Cirrhosae Bulbus. PsbA-trnH also exhibits sufficient amplification efficiency in Fritillariae Cirrhosae Bulbus, but it is difficult to distinguish Fritillariae Cirrhosae Bulbus and its counterfeits accurately. The locus matK cannot be efficiently amplified in Fritillariae Cirrhosae Bulbus. There are many studies on the Fritillariae Cirrhosae Bulbus plant. However, for the high circulation of traditional Chinese medicine on the market, DNA barcodes identification of Fritillariae Bulbus should be studied. Fritillariae Cirrhosae Bulbus in the 2015 edition of Chinese Pharmacopoeia can be used for medicinal purposes, and Fritillaria cirrhosae D. Don, Fritillaria unibracteata Hsiao et K. C. Hsia, Fritillaria przezvalskii Maxim, Fritillaria delavayi Franch, Fritillaria taipaiensis P. Y. Li, and Fritillaria unibracteata Hsiao et K. C. Hsia var. wabuensis Z. D. Liu, S. Wang et S. C. Chen) can be divided into one branch, and the rest of the Fritillariae Bulbus can be divided into different branches. DNA barcodes can not only identify the original medicinal materials but also identify the different parts and residues of medicinal materials. Additionally, we utilized HPLC fingerprint and HCA methods to identify the five Fritillariae Bulbus. The data showed clear differences in the HPLC fingerprints and HCA, allowing for the differentiation of Fritillariae Cirrhosae Bulbus, Fritillariae Thunbergii Bulbus, and Fritillariae Hupehensis Bulbus. However, Fritillariae Cirrhosae Bulbus, Fritillariae Ussuriensis Bulbus, and Fritillariae Pallidiflorae Bulbus could not be distinguished using HPLC fingerprint and HCA methods.ITS and ITS2 can clearly distinguish the five Fritillariae Bulbus types. In the NJ tree, Fritillariae Bulbus can be clearly divided into different branches. The same results can be obtained by using HPLC to identify Fritillariae Bulbus. Fritillariae Cirrhosae Bulbus  were tested for their feasibility for Fritillaria barcoding.Genomic DNA was extracted from dried Bulbus samples using a Plant Genomic DNA Extraction Kit  according to the manufacturer’s protocol. The quality of the extracted DNA samples was verified to ensure their suitability for subsequent amplification. The four candidate barcodes regions ; mobile phase, acetonitrile (A), and 0.02% aqueous triethylamine (B); flow rate, 0.25 mL/min; column temperature, 25 °C; injection volume, 1 µL; and gradient elution program . The parameters of the evaporative light scattering detector were set as follows: Drift tube temperature, 40 °C; sprayer parameters, 40%; gain value, 500; and gas pressure, 30 psi.The instrument was fitted with a Waters ACQUITY UPLCTwo milligrams of each alkaloid reference substance, peimisine (1), verticine (2), verticinone (3), and imperialine (4), were precisely weighed and placed in a 2 mL flask. A known amount of methanol was added to the vial, and the mixture was shaken to ensure uniformity of the prepared mixed reference solution.Approximately two grams of medicinal powder (sieve 4) was precisely weighed, placed in a 100 mL flask, and soaked in a 4 mL aqueous ammonia solution for 2 hours. The solution was then mixed with 60 mL of a mixed solution of trichloromethane-methanol (4/1) and homogenized and refluxed for 3 hours in a water bath at 80 °C before cooling and filtering. The filtrate was placed in an evaporating dish and allowed to dry. The sample was reconstituted in methanol and transferred to a 2 mL volumetric flask. Methanol was added to a known amount, and the mixture was shaken. The solution was filtered through a 0.22 µm microporous membrane filter before HPLC analysis.To determine the precision, three solutions of reference substances with different concentrations were sampled in triplicate. The retention time (RT) and peak area (PA) of each peak were measured, and RSD values were calculated. The retention times and peak areas of fritillarin, sibelin, fritillarin B, and fritillarin A had RSD values ranging from 0.12% to 1.09% and from 0.68% to 3.84%, respectively.Reproducibility was established by extracting six samples of Fritillariae Thunbergii Bulbus and Fritillariae Cirrhosae Bulbus from the same batch according to the abovementioned methods. The peak area of each reference substance was determined in the range of 0.85–2.75% according to the chromatographic conditions described above, which showed that the method had good reproducibility.In the stability experiment, the sample solutions were analysed at 0, 2, 4, 8, 12, 24, and 36 hours. The peak area was recorded. The RSD values of the corresponding concentration of the peak area of each reference substance ranged from 0.71% to 3.47%, indicating that the sample was stable for at least 36 hours.Fritillaria medicinal materials were sampled and analysed according to the preparation method of the solution. Sample analysis was carried out according to the chromatographic conditions described above. The sample injection volume was 1 µL, and chromatographic charts were recorded for 10 min. Meanwhile, the reference solution was injected to determine the retention time of alkaloids. Representative HPLC chromatograms of 10 Fritillaria medicinal materials are shown in Sample determination: a total of 44 batches of 10


Selaginella sinensis (Desv.) Spring has been used for many years as traditional Chinese medicine (TCM) for many years. Recently, ionic liquids (ILs) have attracted great attentions in extraction and separation technology of TCM as a new green solvent. In this paper, microwave assisted extraction-IL (MAE-IL) that extracted amentoflavone (AME) and hinokiflavone (HIN) from Selaginella sinensis was reported for the first time. The contents of two biflavonoids were simultaneously determined by a high performance liquid chromatography (HPLC) method. After different ionic liquids were compared, it was found [C6mim]BF4 had a high selectivity and efficiency. Moreover, the important extraction conditions, including solid-liquid ratio, IL concentration, extraction time, microwave power and radiation temperature, were also investigated and optimized by response surface methodology (RSM) using AME and HIN yields as index. The results showed that the extraction yields of AME and HIN from S. sinensis were 1.96 mg/g and 0.79 mg/g, respectively, under the optimal process parameters . Compared with the conventional extraction methods, MAE-IL could not only achieve higher yield in shorter time, but also could reduce the consumption of solvent. This effective, rapid and green MAE-IL method was suitable for the extraction of AME and HIN. Selaginella sinensis (S. sinensis), the dried whole grass of Selaginella sinensis (Desv.) Spring, grows in Northeast China and belongs to selaginell genus BF4 had remarkable extraction efficiency towards the two targets among these five ILs. Considering the improvement of hydrophobic effect [6mim] BF4 was chosen for extraction of AME and HIN from S. sinensis.The screening of IL’s anions and cations for high extraction efficiency of active ingredients from natural products are considered to be crucial for their various properties and performance . Firstlyshown in A, The yienerated . And thec effect , the conc effect . Based o6mim] BF4 was used as the extractant. Furthemore, the probable influence parameters, including IL concentration, solid-liquid ratio, irradiation time, microwave power and extraction temperature, were evaluated in detail. According to the literature of He et al.  BF4 solutions with 0.2~1.2 mmol/L were compared during the extraction of 8.0 g S. sinensis powders at 300 W for 40 min. As shown in 6mim)BF4 in the range of 0~0.6 mmol/L, which might be that [C6mim] BF4 solutions can easily break the structure of cell membranes, dissolve more AME and HIN and promote the extraction of active gredients. But in the range of 0.6~1.2 mmol/L, the extraction efficiency of AME and HIN was still constantly decreased as a result of the viscosity increase of IL solution [6mim] BF4 concentration of 0.2, 0.4 and 0.6 mmol/L were evaluated for the subsequent RSM optimization.IL concentration can be regarded as the primary influence factor for effective constituents of natural products . The comsolution . Thus, [6mim] BF4 ethanol solution was employed in the extraction of 8.0 g S. sinensis powders at 300 W for 40 min, and the suitable extraction temperature was investigated from 20 to 70 °C in the following investigation. And then it could be found from 6mim] BF4 solution. However, in the range of 50 to 70 °C, the extraction performance of AME and HIN was distinctly reduced, which might be that the two biflavonoids contained thermal-unstable phenolic hydroxyl, and could be oxidized at high temperature  BF4 ethanol solution was used in the extraction of 8.0 g S. sinensis powders at 50 °C and 300 W for 40 min, and the suitable solid-liquid ratio was evaluated from 1:5 to 1:15 (g/mL) in the subsequent experiment. As shown in S. sinensis.Ratio of solid  to liquid (extractant) is key for the extraction process of Chinese herbal medicine, which changes the contact area between solids and liquids, dissolves a lot of the active ingredients and enhances the extraction efficiency by permeating into cells . Here 0.After screening the effects of IL concentration, radiation temperature and solid-liquid ratio, the influence of microwave power on extraction yields of AME and HIN was also studied. In short, low microwave power could result in the incomplete extraction for AME and HIN, but excessive radiation power would be unnecessary and increased energy consumption after reaching complete extraction . Hence, 6mim] BF4 solutions (80 mL) within 10~60 min were chosen and evaluated using the extraction of 8.0 g S. sinensis powders at 50 °C and 300 W. Compared with some traditional methods such as soxhelt extraction and percolation extraction, it is well-known that microwave assisted extraction can shorten radiation time and improve extraction efficiency. In general, if extraction time is too short, it will result in incomplete extraction of target composition; on the contrary, excess time will lead to the unnecessary energy consumption . Thus in1) and HIN (Y2) were presented as the following equation:1, X2 and X3 represented extraction time, solid-liquid ratio and IL concentration, respectively. ANOVA datas of quadratic polynomials were shown in p < 0.0001 and the lack of fit for two biflavonoids were not significant with p > 0.05. This model for AME and HIN indicated a high degree of correlation between the observed and predicted values with R2 = 0.9557 and 0.9656, respectively , methanol, methanol-H2O  and acetone-H2O ) were investigated in detail with several conventional methods. Among them, The established MAE-IL process was compared with the conventional MAE, SE and PE approach in order to evaluate the extraction performance of AME and HIN using ILs. Before different extraction approaches were compared, different extractants , soxhlet extraction (SE) (extraction time 120 min and solvent to solid ratio 15:1 mL/g), and percolation extraction (PE) (extraction time 12 h and solvent to solid ratio 20:1 mL/g).S. sinensis.As shown in S. sinensis and its residue after extraction by MAE-IL. As shown in S. sinensis powders by SEM exhibited a rough and porous cell wall structures and indistinct boundary between different tissues  was successively applied to observe the characterize of  tissues B1,B2. ItIn order to ensure reliable and precise analysis results of MAE-IL extraction, methodological investigation of HPLC, including linearity, stability, precision, repeatability and recovery, must be established using AME and HIN yields as index under the optimized conditions.AME = 346.35X + 3.4667 (R2 = 0.9992) and YHIN = 264.05X + 6.0667 (R2 = 0.9996), respectively, where X was their concentration (μg/mL) and Y was the value of peak area. As shown in R2) more than 0.999, and LOQs (S/N = 10) and LODs (S/N = 3) for AME and HIN of the extracts were less than 0.278 μg/mL and 0.046 μg/mL, respectively. After a series of standard solutions of AME and HIN with different concentration levels were prepared, the linearity was firstly assessed for two biflavonoids and the calibration curves were established by HPLC. The standard curves of AME and HIN were YS. sinensis extract. The stability was assessed on the basis of determination of each analyte at 0, 12, 24 and 36 h at 25 °C, and the relative standard deviation (RSD) of peak area were 0.68% and 1.21% for AME and HIN, respectively, which indicated that the two biflavonoids were stable in IL extract at 36 h. Intraday precision was performed to reused the same analyte six times in the same day for target products, and interday precision was determined on six consecutive days. Intra- and interday variations of the samples were less than 0.73% and 1.75% as RSD values, respectively. Determining the repeatability of IL solution, six same extracts were successively obtained. The extraction yields of AME and HIN had good repeatability with RSD values of 1.34% and 1.72%, respectively, which suggested that the proposed method can be considered suitable for their quantification (see S. sinensis (n = 6). The established method had acceptable recoveries for AME and HIN in the range from 94.01% to 97.98% (RSD = 1.81%) and 97.92% to 101.16% (RSD = 1.88%), respectively. Based on the above results, the proposed analysis methods for quantification of AME and HIN in the extract were credible.Stability, intraday precision, interday precision, repeatability and recovery of the optimal extraction condition were confirmed for each tion see . The recNewly, MAE-IL technology has been successfully used in the extraction of flavonoids, polysaccharides, terpenes, anthraquinones and alkaloids of TCM  for nove6mim]BF4 as an extractant in the optimized process will certainly promote the disruption of the cell walls in S. sinensis and will improve the mass transfer rate of solvent permeation into the cell, thus a large number of target components will be extracted. Meanwhile, suitable IL concentration can be regarded as the primary influence factor for the extraction process. If IL concentration is too high, the extraction yields of the target constituents will constantly decrease because of the viscosity enhancement and the diffusion ability decline of IL solution.First, based on the literature ,38, imidS. sinensis, and then can be quickly converted to heat energy, which will rise rapidly the temperature inside the plant cell. When the pressure inside the cell exceeds the bearing capacity of the plant issue, the plant cell wall will be ruptured. Then, AME and HIN will flow out of the cell and will be dissolved in IL solution at low temperature. Notably, Ding et al. BF4 concentration; B: extraction temperature; C: solid/liquid ratio). As shown in A Box–Behnken design of RSM was used to analyze and optimize the MAE-IL process of two target compounds in regard to three variables . The recovery of two biflavonoids was tested based on the HPLC method described earlier in 18 chromatographic column  at a column temperature of 25 °C using methanol- water  as the mobile phase. The detection wavelength was set at 210 nm and the injection volume of the sample was 10 μL. The standard curves of IL was: Y = 3287.8X + 8.0667 (r = 0.9992) (0.16–0.96 μg/μL).After extraction process, the recovery of two biflavonoids and IL from According to the extraction methods of Chen S D et al. and Eibes G et al. ,44, ethyp < 0.05. After repeated extraction tests were completed (n = 3), mean and standard deviation were calculated. Design Expert 8.0  was adopted for designing and optimizing the process. The analysis of variance (ANOVA) data by RSM was used to analyze the experiment results and predicte values of AME and HIN, which were statistically significant at the level of S. sinensis for the first time. After screening different ILs, it was found [C6mim] BF4 had significant influence on target constituents and was finally chosen as the optimal IL. The results after optimizing MAE-IL conditions by RSM indicated that the extraction yields of AME and HIN could reach 1.96 mg/g and 0.79 mg/g, respectively. In addition, compared with conventional solvent extraction, MAE-IL system showed remarkable characteristics of less solvent, higher efficiency and shorter extraction time, which confirmed that MAE-IL had the potentiality for extracting AME and HIN from S. sinensis. In this work, IL solution combined with MAE was studied in detail on the extraction of AME and HIN from


Concerns have been raised that the transplants performed in the local context at the time of procedures reported in this article  may haveDetails as to the donor sources and methods of obtaining informed consent from donors were not reported in , and wheThe authors did not provide documentation when requested by the journal to confirm that the study had institutional ethics approval. They stated that all organs/tissues were obtained voluntarily for the transplant procedures, but did not provide documentation to support this claim or any further clarification regarding the informed consent procedure or causes of death for organ donors.In addition, in response to journal requests about data availability, the authors did not provide underlying data supporting this study or comment on the availability of the data.The authors noted that many of the original materials requested by the journal to clarify these issues are no longer available.PLOS ONE Editors retract this article.Owing to the lack of documentation to demonstrate this study had prospective ethical approval, insufficient reporting, unresolved concerns around the source of transplanted organs and whether they included organs from prisoners, and in compliance with international ethical standards for organ/tissue donation and transplantation, the The first author notified the journal that all authors agree with the retraction. The other authors either could not be reached or did not respond directly.


This article reviews many current MRE reconstruction methods and discusses the aforementioned differences. The material assumptions underlying the methods are developed and various approaches for noise reduction, regularization, and numerical discretization are discussed. Reconstruction methods are categorized by inversion type, underlying assumptions, and their use in human and animal studies. Future directions, such as alternative material assumptions, are also discussed.Assessment of tissue stiffness is desirable for clinicians and researchers, as it is well established that pathophysiological mechanisms often alter the structural properties of tissue. Magnetic resonance elastography (MRE) provides an avenue for measuring tissue stiffness and has a long history of clinical application, including staging liver fibrosis and stratifying breast cancer malignancy. A vital component of MRE consists of the reconstruction algorithms used to derive stiffness from wave‐motion images by solving inverse problems. A large range of reconstruction methods have been presented in the literature, with differing computational expense, required user input, underlying physical assumptions, and techniques for numerical evaluation. These differences, in turn, have led to varying accuracy, robustness, and ease of use. While most reconstruction techniques have been validated against  CDICurl‐based direct inversionDIDirect inversionFEMFinite element methodLFELocal frequency estimationMDEVMultifrequency dual elastoviscoMREMagnetic resonance elastographyTWETraveling wave expansion.1Tissue stiffness is often affected both directly and indirectly by disease, with common examples being fibrosis, tumor growth, and inflammation. As tissue becomes fibrotic, collagen density increases in the extracellular matrix, leading to a macroscale effect on stiffness.T1 relaxation.Elastography is an imaging technique that infers stiffness by examining a tissue's response to some excitation. This excitation, often externally applied, leads to deformation in the tissue, which can be measured by medical imaging methods such as magnetic resonance (MR) or ultrasound (US). These measured deformations can be used to reconstruct stiffness values by solving equations based on a chosen tissue model that relates these quantities. The calculated values of stiffness  are similar to what is felt during palpation.The first experiments in elastography began with US imaging.MRE has demonstrated success in many areas. Investigations into liver have revealed that MRE is capable of staging liver fibrosiselastogram.Within MRE there are many differing implementations, where considerations include the type of tissue excitation, the hardware required to produce the excitation, acquisition methods, and reconstruction methods. Three common tissue excitation techniques across elastography are quasi‐static deformations, transient waves due to singular pulses, and harmonic wave motion due to a single frequency vibration; however, the most common technique in MRE is harmonic.MRE reconstruction algorithms have been implemented in many ways, with different underlying assumptions and employing varying processes for the inverse solution. Understanding these differences is important, as they effect uniqueness, accuracy, robustness, ease of use, and required computation time. This article discusses these effects while comparing and summarizing MRE reconstruction methods and associated studies currently present in the literature. The theory underlying MRE reconstruction is presented and the applicability of MRE in various human and animal studies is described.In Section 2ρ, and common pairs for the remaining two include the following: (i) the two Lamé parameters, λ and G; and (ii) the Young's modulus, E, and Poisson's ratio, ν. As materials approach incompressibility, the following occur: ν→0.5, λ→∞, and E→3G. For tissue that is nearly incompressible, knowing the shear modulus is therefore essentially equivalent to knowing the Young's modulus.In harmonic MRE, a transducer is placed against a patient and produces single‐frequency waves  that move through an ROI. Due to the small displacements associated with these waves, the linear elasticity or viscoelasticity equations are typically assumed to govern the tissue deformation. An isotropic assumption is also typically made of tissue during MRE, which is usually considered reasonable depending on the tissue type. The isotropic linear elastic equations contain three material parameters. The first is the density, ur, into a steady‐state complex‐valued field, u(x), related by ur=Reu(x)exp(iωt), and reconstruction methods calculate complex values for stiffness, G.The wave displacements are constructed from complex‐valued k‐space MRI data. These data are captured at several time points over the period of the wave (four or eight time points is common). Occasionally, even at this stage, qualitative conclusions can be made regarding the underlying stiffness, as changes in wavelength are sometimes visible and these correspond to changes in stiffness (in the absence of boundary effects). For quantitative results, however, reconstruction is used. Typically, due to the time harmonic excitation, dynamic vibrational analysis is used, which models the displacements and stiffness parameters as complex‐valued entities. The equations, in this form, then also capture effects of viscoelasticity. A discrete Fourier transform converts the time‐dependent real displacements, u, p, G and λ are complex valued. Additionally, p is pressure and ω is angular frequency. The density, ρ, is usually assumed to be that of water, ρ≈1000 kg/m3, when modeling tissue. The shear modulus, G, is often written as G=G′+iG′′, where G′ is the storage modulus and G′′ is the loss modulus. Generally, Equation u and p are unknown. Boundary conditions are also necessary. For example, Dirichlet conditions such as u=u¯ may be specified, where u¯ are known displacements.The isotropic linear viscoelasticity equations areρω2u+∇·G∇u,p∈U×LC2Ω such that, for all w,q∈U0×LC2Ω,U=u|u∈HC1Ω,u=u¯onΓ1 and the test function space U0=w|w∈HC1Ω,w=0onΓ1. Here, w and q are test functions, Ω is the spatial domain, Γ1 denotes the portion of the boundary of Ω where known displacements, u¯, are imposed, and Γ2 denotes the portion where known tractions, T¯, are used.The weak  form of these equations is also noteworthy, as it is the weak form on which the finite‐element method (FEM) operates. The FEM is a popular numerical discretization choice for MRE because, as an integral approach, it reduces the order of differentiation, and thereby may help to reduce noise sensitivity. For example, the incompressible forward problem defined by Equations u, ρ, and ω are known and G, λ, and p are unknown. Boundary conditions may also need to be reconsidered depending on the inverse formulation. Furthermore, only an estimate of u is measured from MR; this is a discrete quantity that contains error (e.g. noise or artifacts), herein denoted u¯i, where i counts over the discrete elements of u¯i, typically one for each voxel. The goal of reconstruction methods is to solve for G, based on the measured u¯i, and, depending on the method, potentially include solutions for either λ or p.However, in MRE an inverse problem is solved, where u¯i, inherently contain noise, as MRI produces images with finite signal‐to‐noise ratio (SNR). A common and straightforward method to reduce noise is to apply a local Gaussian filter directly to the displacement data. Another common approach is local polynomial fitting, also called Savitzky–Golay filtering. From this method, smooth derivatives of the displacement fields can also be computed by using the derivatives of the polynomials calculated during the filtering. These local spatially based filters may have issues near discontinuities and boundaries, but these errors will be localized. Frequency‐based low‐pass filtering is another option, but this may have issues in oddly shaped domains, and, being a global operation, errors may propagate throughout the domain. More advanced denoising techniques have also been applied in MREThe measured displacement fields, ∇p term in Equation ∇λ∇·u in Equation Both compressional and shear waves are present in tissue during MRE and it is the combined displacements from both that are collected by imaging. The assumption of linear viscoelasticity accounts for both types of wave; however, it is the shear modulus, and therefore the shear waves, that elastography is oriented towards. In part, this is due to the shear‐wave speed varying more over different tissue types than the compressional wave speed, but also to the fact that the compressional waves are much faster, which makes balancing considerations like applied frequency and imaging constraints more difficult.ν and E, assuming a near‐incompressible value for ν, and solving for E; (4) apply a high‐pass filter aimed at removing the long‐wavelength compressional wave; and (5) assume incompressibility and solve Equation p in addition to G.Amongst reconstruction methods, there are five common approaches for considering the compressional wave: 1) ignore this term, i.e. assume the gradient of pressure is negligible; (2) apply a discretized curl operator to the displacement data and reconstruct using this curl field, assuming it to be divergence‐free; 3) prescribe one of the parameters, most often by recasting Equation  prescrib ignore tν typically leads to numerical instability, so usually values in the range 0.49–0.499 are chosen. This causes the errors in the reconstructed λ to be of several orders of magnitude. Reconstructed G may be accurate, however there may be errors in regions of strong mode conversion.There are strengths and drawbacks to each of these approaches. Neglecting the pressure term has been shown to lead to errors in the reconstructed stiffness,p increases the number of unknowns, thereby demanding more from the available data. The pressure in some cases may also require some regularization. Two worksWhen applying a high‐pass filter, it is not always the case that the compressional and shear components are well separated in frequency space. The shape of the domain and areas of mode conversion can lead to a lack of separation. Finally, solving for While the preceding discussion has focused entirely on theory assuming harmonic excitation, as this is most common in MRE, some of the methods described in Section 3iterative and direct. In other literature, iterative methods are sometimes called nonlinear inversion (NLI) methods.Reconstruction methods for MRE may be categorized in a variety of ways, but probably the largest division regards the two approaches to solving the inverse problem: Iterative methods solve a nonlinear constrained minimization problem, that is they attempt to minimize the difference between the measured wave field and simulated wave fields found from solving forward problems. During each iteration, a forward problem is solved using a set of stiffness variables calculated from a previous iteration using minimization update techniques. Upon reaching a minimum, or satisfying some convergence criteria, the current stiffness variables are considered to be the solution to the inverse problem. Iterative methods, therefore, are strongly dependent on model assumptions such as initial stiffness values and boundary conditions, as they only consider displacement fields that satisfy the governing equations. Features in the landscape of the stiffness variable space, such as multiple minima or shallow minima, may lead to a lack of uniqueness, slow convergence, or divergence. Regularization techniques are often employed to mitigate these issues, as well as decreasing the likelihood of inaccurate or non‐physical results. These come with the drawback of additional parameters, on which the results will also depend. Iterative methods are currently computationally expensive, due to the many matrix solutions required for computing both the forward solutions and the stiffness variable updates; however, many potential advances may address this. Despite these concerns, iterative methods are a useful approach, due to their relative independence from data quality and their potential for increased accuracy.In contrast, direct methods, while having many benefits, are more dependent on data quality. They solve a linear minimization problem, by assuming that the displacements from the measured wave field are sufficiently accurate to be inserted into the governing equations, leaving the linearly dependent stiffness variables  as the unknowns available to minimize the system. After computing any required displacement derivatives by standard numerical techniques, the system is solved directly for the unknowns. Typically, the resulting matrix system is overdetermined and so is solved by least‐squares matrix inversion. Due to the single solution, these methods require much less computational effort than iterative methods. Other advantages include fewer method parameters and the guaranteed existence and uniqueness of a solution. The solution itself is, however, more sensitive to data quality and any processing parameters, compared with iterative methods.3.1L=0, where u^ are calculated displacements, u¯ are measured displacements, ·X denotes some norm, and the operator, L, is presumably based on the equations of motion presented in Section The goal of minimization in iterative methods is to findThe measured displacement data are often used in two ways within iterative methods. The first is to define the optimal configuration of the displacements calculated from the forward problem, as in Equation G is a vector containing the material parameters, i counts over voxel locations, j counts over the three components of the displacements, and ∗ denotes the complex conjugate. Derivatives of F with respect to each material parameter are computed and an update formula is constructed, typically of the formGn is found by solving (for a Gauss–Newton approach)r is the residual vector and J contains the derivatives of F.One straightforward and common way to solve Equation JTJ, towards a gradient descent system by an adaptively updated weighting parameter. This may be thought of as regularization of the approximate Hessian, but, importantly, this strategy does not change the stiffness variable landscape, only the approach towards a minimum. Considering the form presented in Equation J on the left‐hand side with the identity and typically a multiplier is used to limit the step size. A full Newton's method approach, which would replace JTJ with the Hessian matrix, has not yet been applied to elastography. Other options include quasi‐Newton methods, such as BFGS, which approximate the Hessian as the iterations proceed.A common modification to the Gauss–Newton optimization algorithm is Levenberg–Marquardt.L2 norm of the Laplacian of the stiffness.Regularization of the stiffness parameters is also commonly employed, often by adding some measure of the derivatives of the stiffness to the minimization function, thereby encouraging a smoother result. Tikhonov regularization, for example, involves adding the 3.1.1The application of gradient‐descent methods to elastography has been investigated by Oberai et al,3.1.2ν is set to a near‐incompressible value and E is solved for, both ν and E are solved for, or both λ and G are solved for.A particularly prominent iterative reconstruction method, and one usually oriented towards harmonic MRE, is the subzone technique, proposed by Van Houten et al.in vivo and ex vivo data (Table 4 FEM nodes). Perreard et al5 element meshes with 100 global iterations.)Many updates and extensions to this method have been published. A parallelized 3D implementation was describedta Table . Doyley 3.1.3ν. Later, this approach was modified to utilize total variational regularization.Many other reconstructions based on Gauss–Newton iterations have been published, in addition to the subzone technique. Kallel and BertrandEskandari et al3.1.44 voxels in phantom studies,Baghani et al3.1.5ν set to a near‐incompressible value. A study published later used and extended this method.ν. Fu et alν. As with the TWE approach, the homogeneity assumption significantly reduces computational time.Samani et al3.2Direct methods take advantage of the abundance of data acquired in MRE to solve directly for the stiffness. This leads to a simpler approach than iterative methods, usually requiring fewer parameters and much less computational effort. If stiffness is allowed to vary spatially, then regularization is sometimes still required to stabilize the solution. These heterogeneous direct methods typically solve over the entirety (or large portions) of the domain and attempt to capture the true heterogeneous nature of the stiffness. In contrast, local direct methods assume local homogeneity of stiffness and perform independent solutions on many small subdomains that combine to span the full domain.i could be found by least squares:u¯i is the displacement data vector and (Δ¯u)i is some approximation of the Laplacian of the data at voxel i.While the accuracy of local methods will suffer in regions with significant stiffness heterogeneity, the homogeneity assumption simplifies and stabilizes the methods as well as decreasing computational expense. In the simplest case of local direct inversion, and where the compressional component is assumed to have been removed, the stiffness at voxel 3.2.1Heterogeneous direct methods consider stiffness to vary spatially and invert the governing equations directly with the proper derivatives affecting the stiffness. These methods are less computationally expensive than iterative methods, as only a single solution is required, but are more expensive than local direct methods, as the matrix system is much larger. Allowing for stiffness heterogeneity may lead to more instability and sensitivity in the method, and therefore these methods sometimes require regularization. As with iterative methods, a common regularization approach is Tikhonov, where, again, a measure of the Laplacian of the stiffness is added to the minimization. If pressure is additionally solved for, then this may also be regularized.ν and discretization via FEM.Several methods consider 2D quasi‐static elasticity with near‐incompressible values of Park and ManiattyHonarvar et alA similar method was later introduced in which the curl operator is applied to the equations to remove the pressure term.3.2.2ex vivo and in vivo animal and human studies  perform a pixel‐wise inversion of the homogeneous time‐harmonic linear viscoelasticity equations. This was first suggested in Romano et alOkamoto et alDirect inversion methods have been used extensively in both research and clinical studies. McLaughlin et al3.2.4Combining multiple‐wave data sets corresponding to the application of different vibrational frequencies is one potential avenue for increasing the stability and reliability of MRE, by essentially increasing the amount of data per unknown. This comes with the disadvantages of needing to account for the frequency dependence of stiffness and potentially longer scan times. Papazoglou et al4ex vivo and in vivo human and animal data. A summary of a selection of these studies is provided in Table The methods presented in Section Although the iterative subzone, TWE, and global direct with sparsity regularization methods have been used in a few studies, local direct methods seem to dominate Table Local direct methods are by far the least computationally expensive; however, few publications on these methodsa priori and can affect the resulting elastogram. Iterative methods, being more complicated, are additionally dependent on parameters other than stiffness regularization, such as subdomain size. While the parameter governing the Levenberg–Marquardt procedure is updated during the iterations, the initial choice may still have an effect. Results and comparisons from iterative and heterogeneous methods can therefore be harder to justify if significant parameter adjustment has occurred.Furthermore, local direct methods are usually not dependent on parameters, besides those controlling the initial smoothing of the wave field. While some options may be available to researchers, these methods are typically able to be used out of the box. Methods that consider stiffness heterogeneity, whether direct or iterative, usually require regularization terms to restrain the stiffness. These terms are weighted against the original equations, but the weights of these parameters are difficult to know Reconstruction methods are sensitive to inconsistencies in the wave data, such as noise, but also imaging artifacts or other wave behavior that deviates from material assumptions. It is the regularization mentioned above that decreases sensitivity to these phenomena and allows methods to attain a level of well‐posedness. Local direct methods again excel here. This is due to both the homogeneity assumption, which increases stability and robustness, and the direct approach, which guarantees a unique solution.Although local direct methods dominate the studies in Table in silico and phantom wave data, instead of being tested on more difficult anatomical data. Of course, these broader comparisons require well‐established stiffness results or publicly available MRE data sets. Another option is the development of in silico data sets that properly capture the added difficulty inherent in anatomical data.If iterative and heterogeneous methods can increase ease of use and robustness, they may begin to compete with local direct methods in terms of clinical viability. This may occur through approaches for quality assessment and confidence estimates or through some automatic adjustment of parameters. Perhaps too often, new reconstruction methods, or updates to existing ones, are validated only on MRE reconstruction may also be extended by considering other material assumptions. Anisotropy is a common feature of tissue and so has been included in some reconstructions.Many research directions within MRE are progressing as it continues to strengthen as a diagnostic method. It is becoming more widely used in tangential research and in the clinic through MRE packages available for MR systems. Success has been shown in staging liver fibrosis and potentially in stratification of tumor malignancy and various brain diseases. As precision and accuracy improve, it has the additional potential to replace invasive biopsy procedures for diagnoses. Stiffness reconstruction algorithms have played a vital role in positioning MRE at the forefront of medical imaging research through advances in robustness, accuracy, ease of use, and computational cost. Further improvements in these areas can allow MRE usage to become more widespread by increasing reliability and confidence in the approach.


Comments were made on the article “The Sensitivity, Specificity and Accuracy of Warning Signs in Predicting Severe Dengue, the Severe Dengue Prevalence and Its Associated Factors” found in the journal “International Journal of Environmental Research and Public Health” based on the CASP Checklist’s guide for the assessment of diagnostic tests. To the Editor,We have reviewed with great interest the article published by Mohd Hanief Ahmad, et al. in the "International Journal of Environmental Research and Public Health", in which you are the editor . The stuNevertheless, when reviewing the study using the CASP Checklist’s guide for diagnostic studies , we founWe are also concerned that records of 2607 patients who met the definition of confirmed dengue cases were not used in the analysis; instead, a sample of only 700 patients was chosen. Since a sample size or power calculation is not included, we do not know if this number was adequate to find significant differences in the subsequent analysis. Even if the sample was chosen randomly and was proportional to the months of the year, perhaps it could be.We could also appreciate that, in the data analysis of the mentioned study, odds ratios (ORs) were used to evaluate the association with the independent variables. This measure of association can be used in cross-sectional studies as long as the prevalence of the outcome variable is low; some authors suggest 10% or less. In this case, with the prevalence of severe dengue being 4.9%, we believe that the use of ORs does not excessively affect the estimation of the risk made . ConcernFinally, having a robust study is especially important when the results reported disagree with what has already been published in the scientific literature. For example, the authors found no association between severe dengue with age and comorbidities, factors widely described in the literature . We beli


In the Results subsection of the Abstract, there is an error in the third sentence. The correct sentence is: IVRT increased with age and on univariate analysis was not only inversely correlated with EDExc and e`, but also with SExc.In the first paragraph of the Relations of LVEDL with age, SExc, EDExc and e`subsection of the Results, there is an error in the first sentence. The correct sentence is: On univariate analysis, LVEDL was inversely correlated with age , positively correlated with BSA , and was larger in males (p = 0.003).In the first paragraph of the EDExc as a dependent variable subsection of the Results, the third sentence should be removed. The correct first paragraph of the EDExc as a dependent variable subsection of the Results is: Selected univariate correlates of septal and lateral EDExc are shown in Table 6 and scatter plots showing the relationship of EDExc with SExc are presented in Fig 2. Septal and lateral EDExc were both positively correlated with BSA, SExc and LVEDL, and inversely correlated with age, IVRT and heart rate. Lateral EDExc was also inversely correlated with diastolic BP, whereas an inverse correlation of septal EDExc with diastolic BP was weaker and only borderline significant. In multivariate models none of sex, BSA or LVEDL were independent predictors of septal or lateral EDExc when combined with the respective SExc and these variables were not included in further modelling. In combination, IVRT and heart rate were independent determinants of EDExc  and explained 43–67% of the variances of EDExc.In the second paragraph of the EDExc as a dependent variable subsection of the Results, there is an error in the eighth sentence. The correct sentence is: In subsequent analysis, that there was only a minor contribution of IVRT to SExc in the prediction of EDExc could be explained by the presence of univariate inverse correlations of SExc with IVRT for both the septal and lateral walls .In the first paragraph of the e`as a dependent variable subsection of the Results, the third sentence should be removed. The correct first paragraph of the e`as a dependent variable subsection of the Results is: Univariate correlations of e`with selected variables are shown in Table 8 and scatter plots showing the relationship of e`with EDExc are presented in Fig 3. Both septal and lateral e`were positively correlated with BSA, SExc, EDExc and LVEDL and inversely correlated with diastolic BP, IVRT and age. Lateral e`was also inversely correlated with heart rate, but an inverse correlation of septal e`with heart rate was only borderline significant. In multivariate models neither BSA nor LVEDL were independent predictors of septal or lateral e`once the respective EDExc was included in the model and these variables were not included in subsequent modelling.In the second first paragraph of the e`as a dependent variable subsection of the Results, there is an error in the third sentence. The correct sentence is: The addition of diastolic BP to EDExc resulted in an increase in 3% of the variance of septal e`explained, but BP was not a significant contributor in the model of lateral e`.In