Data sharing in multicenter medical research can improve the generalizability of research, accelerate progress, enhance collaborations among institutions, and lead to new discoveries from data pooled from multiple sources. Despite these benefits, many medical institutions are unwilling to share their data, as sharing may cause sensitive information to be leaked to researchers, other institutions, and unauthorized users. Great progress has been made in the development of secure machine learning frameworks based on homomorphic encryption in recent years; however, nearly all such frameworks use a single secret key and lack a description of how to securely evaluate the trained model, which makes them impractical for multicenter medical applications.The aim of this study is to provide a privacy-preserving machine learning protocol for multiple data providers and researchers . This protocol allows researchers to train models and then evaluate them on medical data from multiple sources while providing privacy protection for both the sensitive data and the learned model.We adapted a novel threshold homomorphic encryption scheme to guarantee privacy requirements. We devised new relinearization key generation techniques for greater scalability and multiplicative depth and new model training strategies for simultaneously training multiple models through x-fold cross-validation.Using a client-server architecture, we evaluated the performance of our protocol. The experimental results demonstrated that, with 10-fold cross-validation, our privacy-preserving logistic regression model training and evaluation over 10 attributes in a data set of 49,152 samples took approximately 7 minutes and 20 minutes, respectively.We present the first privacy-preserving multiparty logistic regression model training and evaluation protocol based on threshold homomorphic encryption. Our protocol is practical for real-world use and may promote multicenter medical research to some extent. In recent years, researchers have proposed strong requirements for the quality of medical research as it continues to progress, which has promoted the development of multicenter research. Compared with single-center research, multicenter research has many significant advantages, including enabling specific analyses for which no single institution has sufficient data, such as on a rare disease; providing medical data from different locations with diverse demographics, which increases the reproducibility and generalizability of the research; and generating pooled medical data that enables new discoveries that cannot be elucidated from any individual data set ,2. In adHowever, data sharing during multicenter research may increase privacy security risks. As medical data are highly sensitive, the leakage of sensitive information will lead to severe consequences, such as financial loss, social discrimination, and unauthorized data abuse, which can harm both patients and medical institutions . As a reLogistic regression is a widely used machine learning approach in various medical applications, such as prognostic prediction, disease diagnosis, and decision-making support . For exaMultikey homomorphic encryption, first proposed by López-Alt et al , allows In this study, we propose a privacy-preserving multicenter research protocol using secure logistic regression, consisting of 3 primary entities: researchers, a service provider, and data providers, in which medical data are horizontally distributed. Our proposed protocol supports not only model training but also the evaluation of the trained model in a secure manner. The protocol guarantees the privacy of both the sensitive data for the data providers and the trained model for the researchers during model training and trained model evaluation. To satisfy privacy requirements, we apply threshold homomorphic encryption and propose a new relinearization key generation process that increases scalability and multiplicative depth. The proposed protocol has been implemented and tested with simulated real-life scenarios. The experimental results demonstrate that our protocol is efficient and practical for real-world applications.Our proposed protocol includes 3 primary entities as shown below. The architecture of the proposed protocol is shown in These include institutions  who hold medical data and are willing to provide these data to the service provider for public use so long as the privacy of the data is preserved. To share medical data, the data providers must obtain patient consent if the local law requires so. Upon receiving the researchers’ requests from the service provider, the data providers can decide whether to accept or refuse. To allow researchers to obtain correct research data, all data providers must implement data standardization to transform the data into a common format, such as the Observational Medical Outcomes Partnership common data model from the Observational Health Data Sciences and Informatics collaborative .This refers to an entity that (1) provides storage for encrypted data and research information, (2) performs the most computationally expensive part of the privacy-preserving logistic regression, and (3) performs information transfer among the data providers, the service provider, and the researchers. In addition, an interactive website is deployed by the service provider for researchers to conduct their studies in a secure manner and for data providers to authorize certain research requests.This includes the individuals or organizations who want to conduct research on multiple data providers’ data sets. Researchers submit their requests to the service provider, which are then sent to the data providers for further processing.As we use threshold homomorphic encryption to guarantee data and model security, in our proposed protocol, one public key corresponds to multiple secret keys, and different secret keys are distributed to different data providers and researchers. Furthermore, we assume that there exist at least one honest party and some semihonest adversaries that are capable of reading the internal information of the colluding parties while not deviating from the defined protocol .ix, iy), for i=1,...,N, where ix denotes a vector of input features ix= and iy is the class label. We then have:Logistic regression is a classification algorithm that is widely used in medicine, including for disease diagnosis, clinical decision support, and risk assessment. Suppose a data set consists of pairs (iTβx), β= are the model parameters. By training a logistic regression model through minimization of the following cost function, we can obtain the optimal model parameters:In the sigmoid function σ–based, somewhat homomorphic encryption scheme, called Brakerski/Fan-Vercauteren (BFV) and which supports a limited number of additions and multiplications, to perform secure multiparty logistic regression ,26. The The details of the threshold variant of the BFV scheme are described as follows. The security and noise analysis of the scheme are provided in λ): takes the security parameter λ as an input and returns the public parameterization param, including the degree of polynomial modulus n, the coefficient modulus q, the plaintext modulus t, and the  distribution .setup is the ciphertext space of param.THE.keygenSP(param): the service provider samples a ← Ri samples si ← D1, ei ← D2, sets si as its secret key and outputs its public key pki=[−(a · si+ei)]q. Let subscript *co denote the combined key. The combined public key pkco among parties p1,...,pz is then computed as follows: THE.keygenSkpk: each party p1,...,sz): the parties together with the service provider generate the combined relinearization key rlkco. As the generation of the relinearization key is rather complicated, we will show the details of this step later.THE.keygenRelin: This takes a polynomial m∈Rt as the input, where Rt is the plaintext space of the param. Let pkco=(pkco(0), pkco(1)) and Δ=⌊q/t⌋, and sample u ← D1 and  ← D2, then return:THE.encrypt: given a circuit C, a tuple of ciphertexts encrypted by the same public key, and the corresponding relinearization key, this outputs a ciphertext cout. The procedure for homomorphic addition and multiplication is the same as that in the original single-key BFV scheme.THE.eval: given the ciphertext c=(c(0), c(1)) encrypted by pkco and the corresponding secret keys, sample  ← Dsmg. Here, the subscript *smg means that the variance of the noise distribution is much larger than that of the input ciphertext noise distribution to guarantee circuit privacy through smudging techniques ×[c(0x) ~ c(dx)] // Here, c(0x)=13: d+1x, cv, c(0gra) ~ c(dgra), 1s1 ~ zs1, copk1 // See details in (Input: tails in gra(1) ~ gra(10) (unencrypted gradients)Output: All data providers do:0e ~ de ← random noise vectors whose size equals d+1x1: E(1) ~ E(10) ← zero vectors whose size equals d+12: i=1 to size(d+1x)3: For j=1 to d+14: For E((d+1x(i)+cv−1) mod 10+1)(j)+= j−1e(i)5: 6: End forE(1) ~ E(10) are sent to the researcher7: End for // e’ ← CRT-batchingEncode(0e ~ de)8: c(0e) ~ c(de) ← THE.encrypt // c(0e) ~ c(de) are sent to the service provider9: Service provider does:c’(0gra) ~ c’(dgra) ← c(0gra) ~ c(dgra)+c(0e) ~ c(de)10:All parties do:0gra’ ~ dgra’ ← THE.decrypt(c’(0gra) ~ c’(dgra), 1s1 ~ zs1) // To ensure only the researcher obtains the plaintext result, data providers’ and researcher’s partial decryption shares are added at the service provider and the researcher, respectively.11:Researcher does:gra(1) ~ gra(10) ← zero vectors whose size equals d+112:0gra’’ ~ dgra’’ ← CRT-batchingDecode(0gra’ ~ dgra’) // Decoding result is vectors whose size equals d+1x.13:i=1 to size(d+1x)14:For j=1 to d+115: For gra((d+1x(i)+cv−1) mod 10+1)(j)+= jgra’’−1(i)16: 17: End for18:End forgra(1) ~ gra(10) −= E(1) ~ E(10)19:copk1 and sent to the service provider.Once the model training is completed, all involved data providers encode their own research data for each fold into CRT-batched polynomials whose slots are randomly chosen to contain samples. In the meantime, the data providers also generate vectors containing information about whether a certain slot contains a sample and encode them into CRT-batched polynomials. For instance, for a CRT-batched polynomial containing samples in slots , the vector should be . These polynomials are then encrypted by 3. Second, in the slots containing samples, we sample noise from a uniform distribution  whose corresponding values are  in the scaled down plaintext. In When all the aforementioned preparations are completed, the model evaluation starts, as shown in c(1) ~ c(10) (10 encrypted folds of research data), c(1)(d+1x) ~ c(10)(d+1x) (encrypted vectors indicating whether a certain slot contains a sample), β(1) ~ β(10) (trained sets of parameters), 1s1 ~ zs1 (secret keys), copk1 (combined public key)Input: TP, FP, TN, FN Output: Researcher does:FD=1 to 101: For c(0β) ~ c(dβ) ← THE.encrypt(β(FD), copk1) // c(0β) ~ c(dβ) are sent to the service provider2: σ // See  : (max(3G)–min(3G))/100 : max(3G)4: For X ← empty vector5: iσ in σ6: For-each predictive value X.push_back(if(iσ≥V))7: 8: End for-eachX’ ← CRT-batchingEncode(X)9: c(TP), c(FP), c(TN), c(FN) ← c(FD)(y)×X’×c(FD)(d+1x), (1−c(FD)(y))×X’×c(FD)(d+1x), (1−c(FD)(y))×(1−X’)×c(FD)(d+1x), c(FD)(y)×(1−X’)×c(FD)(d+1x) // These 4 ciphertexts are sent to the service provider10: TP’, FP’, TN’, FN’ // See 12: TP, FP, TN, FN ← TP’’−sum(TPe), FP’’−sum(FPe), TN’’−sum(TNe), FN’’−sum(FNe)13: TP, FP, TN, FN // under fold FD and predictive value threshold V14: output 15: End for16:End forc(1)(x) ~ c(10)(x), d+1x(1) ~ d+1x(10), c(0β) ~ c(dβ), FD, copk1, 1s1 ~ zs1 // See details in Output: Service provider does:c(Tβx) ← c(0β)+c(1β)×c(FD)(1x)+...+c(dβ)×c(FD)(dx)1: c(G) ← G3(c(Tβx)) // G3 is an integerized sigmoid function2: All data providers do:e ← random noise vectors whose size equals d+1x(FD)3: e’ ← CRT-batchingEncode(e)4: c(e’) ← THE.encrypt // c(e’) are sent to the service provider5: Service provider does:c’(G) ← c(G)+c(e’)6: All parties do:σ ← CRT-batchingDecode(THE.decrypt(c’(G), 1s1 ~ zs1)) // The same as in (d+1x) ~ c(10)(d+1x), FD, copk1, c(TP), c(FP), c(TN), c(FN), 1s1 ~ zs1 // See details in Output: All data providers do:TPe, FPe, TNe, FNe ← random noise vectors whose size equals to c(FD)(d+1x) // The sums of noises sum(TPe), sum(FPe), sum(TNe), sum(FNe) are sent to the researcher1: TPe’, FPe’, TNe’, FNe’ ← CRT-batchingEncode2: c(TPe’), c(FPe’), c(TNe’), c(FNe’) ← THE.encrypt, copk1) // These encrypted noises are sent to the service provider3: Service provider does:c’(TP), c’(FP), c’(TN), c’(FN) ← c(TP)+c(TPe), c(FP)+c(FPe), c(TN)+c(TNe), c(FN)+c(FNe)4: All parties do:TP’, FP’, TN’, FN’ ← THE.decrypt((c’(TP), c’(FP), c’(TN), c’(FN)), 1s1 ~ zs1) // The same as in , false positives (FPs), true negatives (TNs), and false negatives (FNs) for the 10 folds and different predictive value thresholds, which should be sufficient to evaluate the trained model via 10-fold cross-validation.In this section, we consider the following aspects to assess the performance of our proposed multicenter secure logistic regression protocol: (1) Security analysis: security of sensitive research data and learned model; (2) accuracy loss: the loss in accuracy during the model training and evaluation with respect to the nonsecure method with real medical data; (3) model training and evaluation time: the time needed to perform 10-fold cross-validation with real medical data; and (4) scalability: how the model training and evaluation time increases as the size of the data increases in the synthetic data set.The biomedical data sets used for the experiments are shown in n is a power of 2, whereas the coefficient moduli in param1 and param2 are products of 8 and 5 distinct primes, respectively, where every prime P is at most 60 bits long and satisfies P=1 (mod 2n), which makes the NTT accessible. The plaintext modulus in param1 also satisfies t1=1 (mod 2n), allowing for the implementation of CRT batching.To set the homomorphic encryption parameters, we select the following parameters to guarantee sufficient security, as shown in To simulate a real-world scenario, we place the data providers, the researcher, and the service provider on different machines. For the data providers and the researcher, we use PCs with a 2.2-GHz Intel Core i7-8750H processor and 16.0 GB RAM (Windows 10 Enterprise). For the service provider, we use a server with a 2.3 GHz Intel Xeon Gold 6140 processor and 128.0 GB RAM (Linux 3.10.0). The secure logistic regression protocol is implemented in C++ using Microsoft SEAL v3.0 and is publicly available at GitHub , where wIn our protocol, security means that corrupted parties will not be able to obtain sensitive data or learned models from honest parties. Here, we show the security of our protocol from the following 2 aspects: (1) honest parties’ secret keys will not be obtained by the corrupted parties so that no ciphertext will be decrypted illegally, including the encrypted data, model parameters, and any other intermediate results and (2) if the researcher is an adversary, he or she cannot obtain any meaningful information about honest parties’ individuals from the unencrypted intermediate results.S that, when provided only with the adversaries’ input and output, can simulate the adversaries’ view in the protocol, and the simulated view is computationally indistinguishable from the real view. Suppose there are z parties. Let A denote the adversaries, defined as a subset of at most z −1 corrupted parties, and H denote the honest parties.To demonstrate the security of the secret keys, we use the simulation paradigm described in the study by Goldreich , that isS can simulate the adversaries’ view of public key shares  by randomizing these shares under 2 constraints: (1) the simulated shares must sum to copk(0) and (2) the adversary shares must be equal to the real shares. S can compute this sharing as follows:In the generation of the combined public key, H|>1, there is no efficient algorithm that can distinguish between the simulated and real shares in H because of the decision-RLWE problem. When |H|=1, S computes the real shares of the honest party. However, because both is and ie are private inputs from party ip, the adversaries cannot find the secret key of the honest party because of the search-RLWE problem.When |c=(c(0), c(1)), during the decryption process, S can simulate the adversaries’ view of the decryption shares  by randomizing these shares under 2 constraints: (1) the simulated shares must sum to μ–c(0) and (2) the adversary shares must be equal to the real shares:Given the ciphertext H if the researcher is uncorrupted. However, if the researcher becomes an adversary, they can extract the noise of c as follows:When considering the distribution of the simulated and real views alone, the RLWE assumption is sufficient to ensure the security of secret keys of e’ is the noise of c, which should be unknown to the researcher; otherwise, the RLWE assumption will be broken and the secret keys of the honest parties may be exposed to the researcher. Let 2cvar denote the variance of a centered Gaussian distribution that e follows and 2smgvar denote the variance of smgD, which is used to generate ie. Thus, as long as the ratio 2cvar/2smgvar is negligible, the following 2 distributions are statistically indistinguishable, which means that e’ is unknown to the researcher and that the researcher cannot obtain H’s secret keys:where First, during model training, all data providers apply one-time-use noise to mask the encrypted gradient before decryption, meaning that even if only one data owner is honest, it will not lead to the disclosure of the gradients of the individuals.iσ ∈ , the probability of recovering the research data is computed as follows:Second, during model evaluation, the researcher will inevitably obtain CRT-batched polynomials containing the predictive values for each sample. Given a masked predictive value jN is the number of samples whose predictive value belongs to , ejN is the number of empty slots whose value belongs to , and piN is the number of all possible combinations of feature values whose predictive value belongs to . Therefore, as long as either of these 2 terms is sufficiently small, it is impossible for the researcher to recover the feature values.Here, Furthermore, because the encrypted  information of samples under different predictive value thresholds is also masked by all data providers before being sent to the researcher, the researcher cannot obtain the label of any specific sample.α=.1, 45 iterations). Compared with that of the nonsecure protocol, a relatively small loss of accuracy was observed in our protocol, which was not statistically significant . The average receiver operating characteristic curves from the 10-fold cross-validation are plotted in In Furthermore, in We show the time consumption of the 10-fold cross-validation for the 2 different data sets in Here, we compare our protocol with the SecureLR protocol by Jiang et al , which id, for the sake of simplicity, we suppose that every data provider encrypts (d+1) polynomials. As the number of data providers increases, the computation times of both the model training and evaluation increase proportionally, whereas there is no increase in the transfer time of the model training because the size of the transferred data (encrypted parameters and gradients) is only related to the number of features. Similarly, because there is no relationship between the number of data providers and the transfer of the encrypted , the transfer time of the model evaluation increases very less. As the number of features increases, the computation and transfer times of the model training increase proportionally, whereas the computation and transfer times of the model evaluation increase only slightly because the majority of the model evaluation involves the computation of  information under different predictive value thresholds, which is not related to the number of features.To test our protocol’s scalability, we use a synthetic data set with different numbers of data providers and features, as shown in As researchers cannot obtain unencrypted research data, they may have difficulty choosing the proper hyperparameters, especially the learning rate. Despite a slightly broader range of learning rate selection, the setting of the learning rate is still very important in our privacy-preserving multicenter logistic regression protocol because compared with the nonsecure protocol, our protocol still has a considerable time cost. In our proposed protocol, interactions exist among the service provider, the data providers, and the researcher, allowing the researcher to obtain the plaintext model parameters in every iteration. As a result, the researcher can easily judge whether the hyperparameters are set properly according to the trend of the model parameters. Moreover, the researcher can halt the model training in the early stages, which results in less waste of computational resources. However, to implement the web-based protocol, clients must be installed on all the data providers’ and researchers’ machines, which must be kept online during the entire process of model training and model evaluation, leading to an additional consumption of network bandwidth.ω to encode a real number as a polynomial, which may affect the use of CRT batching (the most important optimization technique in our protocol), whereas Chen et al [scale to avoid destruction of the plaintext by the smudging noise, which greatly reduces the multiplicative depth of the circuit.There is a trade-off between computation and transfer consumption in our protocol. Although some solutions use fully homomorphic encryption to avoid decryption during model training ,15, our en et al  scheme, Our proposed protocol has a few limitations. First, to make the privacy-preserving logistic regression realistic, this protocol requires a high-speed and stable network. Second, as the BFV scheme is based on integers, before encryption, all floating-point numbers must be scaled up and rounded to integers. A larger SF can support a higher level of precision but will also result in higher computation and storage costs for a given security level. Third, in a real-world scenario, a single patient may have multiple medical records across different data providers, which rarely occurs when data providers are far apart but is not uncommon when data providers are located in the same region . Therefore, in the latter case, further research on privacy-preserving identification and deduplication is required to ensure that there are no duplicate medical records to affect the analysis results. Furthermore, this study mainly focuses on technical issues and thus does not delve into matters related to ethics and law, which are also very important in multiparty medical research.In this paper, we propose the first privacy-preserving multiparty logistic regression model training and evaluation protocol based on threshold homomorphic encryption. We conduct experiments in simulated real-life scenarios, and the results demonstrate that the proposed protocol is practical for real-world use. We believe that our work can help medical institutions eliminate privacy leakage concerns during data sharing, promote multicenter medical research, and thus improve the use of medical data to some extent.In the future, we will extend our tools to be more practical. As the BFV homomorphic encryption scheme does not have indistinguishability under chosen ciphertext attack security, additional security technology, such as hashing, should be integrated into the tools to prevent malicious attackers from tampering with the ciphertexts. More privacy-preserving statistics and machine learning methods will be added to our tools to facilitate considerably enhance flexibility in secure multicenter research. Furthermore, we will improve the efficiency of our tools using graphics processing unit or field programmable gate array acceleration.


Bactericera cockerelli  is the main vector of ‘Candidatus Liberibacter solanacearum’ on potato and tomato crops in North America and New Zealand; and is considered a threat for introduction in Europe and other pest-free regions. This study describes the design and validation of the first species-specific TaqMan probe-based real-time PCR assay, targeting the ITS2 gene region of B. cockerelli. The assay detected B. cockerelli genomic DNA from adults, immatures, and eggs, with 100% accuracy. This assay also detected DNA from cloned plasmids containing the ITS2 region of B. cockerelli with 100% accuracy. The assay showed 0% false positives when tested on genomic and cloned DNA from 73 other psyllid species collected from across Europe, New Zealand, Mexico and the USA. This included 8 other species in the Bactericera genus and the main vectors of ‘Candidatus Liberibacter solanacearum’ worldwide. The limit of detection for this assay at optimum conditions was 0.000001ng DNA (~200 copies) of ITS2 DNA which equates to around a 1:10000 dilution of DNA from one single adult specimen. This assay is the first real-time PCR based method for accurate, robust, sensitive and specific identification of B. cockerelli from all life stages. It can be used as a surveillance and monitoring tool to further study this important crop pest and to aid the prevention of outbreaks, or to prevent their spread after establishment in new areas.The accurate and rapid identification of insect pests is an important step in the prevention and control of outbreaks in areas that are otherwise pest free. The potato-tomato psyllid  Bactericera cockerelli , (commonly known as “Potato Psyllids” or “Tomato-Potato Psyllid”), is a major pest of cultivated Solanaceous crops including potato and tomato Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: NoReviewer #2: NoReviewer #3: No**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: This manuscript describes a qPCR assay to identify potato psyllid intercepted in shipments. The assay is paramount to Europe's ability to detect potential introductions of this psyllid, which would be harmful to agricultural production. The authors describe the assay and confirmed that it does not amplify the ITS gene of other psyllids.My major concern for the manuscript is that it is overwritten and over-interpreted. The study is very simple - qPCR assay to detect potato psyllid - yet the text is over 50 pages long, includes unrelated information in the introduction, and includes an overly long discussion. The manuscript should be re-written to focus only on the assay and its use in trade commodities. Specific comments are provided in an attached document. I will apologize for my handwriting.Reviewer #2: In this manuscript, the authors describe the design and validation of the first species-specific TaqMan probe-based real-time PCR assay, targeting the ITS2 gene region of Bactericera cockerelli, for robust and quick identification of the potato-tomato psyllid B. cockerelli, the main vector of ‘Candidatus Liberibacter solanacearum’ on potato and tomato crops in Central and Northern America and New Zealand. The authors examined false-positive rates in non-target psyllid species and false-negative rates in target species, including B. cockerelli at different life stages. The assay also compared amplification efficiency at different MgCl2 concentrations, primer concentrations, and annealing temperatures, and determined the detection limit at optimum conditions. The assay was designed and presented in a very robust way, however, I have some minor concerns the authors need to look into before the manuscript can be accepted.Minor Concerns:1. Data Availability: The authors need to add accession numbers for their sequence data.2. Page 8 Line 163: What part of the body is used for micro-dissection to extract DNA? The authors should describe the micro-dissection procedure in more detail rather than only citing the papers.3. Page 8 Line 172: “For amplification of ITS2 primers CA55p8sFcm-F and CA28sB1d-R [60] and for amplification of CO1 gene regions arthropod barcoding Primers LCO1490 and HCO2198 [61].” The authors should check the grammar here. It is not a complete sentence. It could be “For amplification of ITS2, primers CA55p8sFcm-F and CA28sB1d-R [60] were used, and for amplification of CO1 gene regions, arthropod barcoding Primers LCO1490 and HCO2198 [61] were used.”4. Page 10 Line 204: “DNA was extracted as above using the non-destructive method, amplified and cloned into competent Escherichia coli cells using the TOPO TA cloning kit (Thermo-Fisher).” The authors should specify what genes (ITS2 or CO1?) they amplified for cloning, and what restriction enzyme (EcoRI?) they used to linearize the plasmid.5. Page 10 Line 212: The authors need to list the real time PCR cycling conditions here, for example XX degrees for XX seconds.6. Page 10 Line 223: “All reactions with non-target psyllid DNA were run in conjunction with a TaqMan Exogenous Internal Positive Control Reagent Kit (Applied Biosystems) to ensure false positives were not obtained due to inhibition within the reaction”. Here, “ensure” should be “rule out the possibility that”.7. Page 11 Line 226: “DNA from all non-target psyllids was sequenced to ensure psyllid DNA was present in all reactions to rule out false negatives due to inefficient DNA extraction.” What DNA was sequenced? PCR product from ITS2 or CO1? The authors need to specify.8. Page 11 Line 239: “6 subsequent dilutions were made. Stock DNA 10 ng/μl was linearised using EcoRI restrictions enzyme (New England Biolabs),” Here “6 subsequent dilutions” should be “8 subsequent dilutions”, according to the nine point 10-fold dilution series mentioned on Page 11 Line 236.9. Page 12 Line 252: “A six point 1:10 dilution series starting at 10ng/μl was used with each dilution being performed in triplicate.” Here, “six point” should be “nine point” according to Page 11 Line 236.10. Page 12 Line 263: “For each tested parameter, optimization was performed across an eight point 1:10 dilution series starting at 10ng DNA.” Here, “eight point” should be “nine point”, “10ng” should be “10ng/μl”.11. In Supplementary table S1, green and red color coding should be explained in the text. What does TBC mean? Accession numbers should be given for all the sequences. Accession numbers in Table 3 should also be given and TBC should be explained.12. Page 14 Line 289: “CO1 genes showed higher similarity and generally less conserved and variable regions compared to ITS2 regions.” Here “less conserved and variable” should be “less variable”.13. Page 17 Line 310: “0.2 µ/mol” should be “0.2 µM”.http://scienceprimer.com/copy-number-calculator-for-realtime-pcr was used.” Here a hyperlink should be created. According to the link and the formula given, 0.00001ng DNA equals 4.879×10000 copies, if length of gene region is considered 187bp . However, the authors calculated that it equals to 200bp. Please double check the calculation.14. Page 18 Line 324: “The copy number calculator available at 15. Page 18 Line 337: “At primer concentration, 0.5 μM the assay was less sensitive only amplifying up to 0.001 ng DNA.” It should be “At primer concentration 0.5 μM, the assay was less sensitive only amplifying up to 0.001 ng DNA.”16. Page 18 Line 338: “At higher primer concentrations (0.5 and 1.0) the assay showed higher sensitivity” Here “(0.5 and 1.0)” should be “(1.0 μM)”.17. Page 19 Line 350: “The precision of the assay was lower at higher MgCl2 concentrations 6mM and 8mM (Supp Tab. S3).” Here “6mM and 8mM” should be “7.5mM and 9mM”.18. Page 19 Line 354: “Reactions at 58 °C were 10 to 100-fold less sensitive than reactions at 58 °C.” Here it should be “Reactions at 58 °C were 10 to 100-fold less sensitive than reactions at 64 °C.”19. Page 20 Line 367: “We have designed and validated the first species-specific, qualitative real-time PCR TaqMan assay for B. cockerelli by using the comparison of 73 non-target species to identify unique gene regions that were suitable for primer/probe design and species differentiation.” Here “qualitative” should be “quantitative”.Reviewer #3: The manuscript presents a new real time assay that will make identification of the key pest commonly known as potato-tomato psyllid easier and faster. The assay has been rigorously developed, with appropriate controls, replication and sample size. The specificity of the assay is fairly assured by the inclusion, in its development and validation stage, of numerous non target species, including 9 congeneric species, representing about 30% of known European Bactericera taxa. The manuscript is well written, with thorough introduction and discussion, and methods and results clearly presented. There are only some minor issues that should be dealt with before the manuscript can be accepted for publication:- Page 8 line 175: please replace amount of primers used with final concentration of primers (or add this)- Page 10 line 213: please add cycling conditions of real time PCR, as done for CO1 and ITS2 amplification- Table 1: should include also B. cockerelli, so to include fragment size of amplicons for this species. In alternative, fragment sizes can be added to the main textTable 3: not clear what the "/" symbol in the CO1 column means- Page 17 line 310: please check spelling of concentration- Page 17 line 316: numbers seem not to add up: how many technical replicates were used per sample?- Page 18 line 323: I have tried the formula myself using the concentration (0.00001 ng) and fragment size (187 bp) specified by the authors, but I get a quite different number of ITS2 copies . Please double check, and add actual numbers to the formula.Of some concern is the author's answer to the data accessibility question. Authors stated that they are not going to make all data available, with a generic "Some restrictions will apply". Please explain what data will not be made accessible and why.**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool, Attachmentdoc07744220200113085906.pdfSubmitted filename: Click here for additional data file. 18 Feb 2020Dear Dr Sean Michael Prager,Please find enclosed our revised manuscript entitled “A diagnostic real-time PCR assay for the rapid identification of the tomato-potato psyllid, Bactericera cockerelli  and development of a psyllid barcoding database”. We thank you and the reviewers for your careful review of our submitted manuscript and the opportunity to resubmit an improved version. We find the comments to be fair and constructive and have helped to improve the final manuscript. Please see below our responses to points raised by the reviewer’s comments and the amendments we have made to the final manuscript. We provide a copy of the resubmitted manuscript with track changes and track changes accepted. Line numbers refer to those given in the resubmitted manuscript with track changes accepted.We hope that you will consider this revised manuscript of a high enough standard to be published in PLOS ONE. Yours Sincerely,Dr Jason C Sumner-Kalkun• Thank you for considering our work for publication in your journal. We found all reviewer comments to be useful and constructive and appreciate you overall assessment of the manuscript. We are pleased to have the opportunity to resubmit an improved version. We have made considerable efforts to condense the introduction and discussion section to include only relevant information and to streamline the manuscript. We agree that there was some duplication and repetition in the discussion, and it has been re-written accordingly. We decided, due to the technical nature of the paper that a separate results and discussion section was more appropriate. We have addressed the reviewer concerns regarding data availability and all sequence data has been uploaded to GenBank and is now free to be made publicly available. We hope that our amendments are deemed adequate to meet the high standards of PLOS ONE and are excited about the possibility of publishing with you. REVIEWER COMMENTS TO AUTHORReviewer #1: This manuscript describes a qPCR assay to identify potato psyllid intercepted in shipments. The assay is paramount to Europe's ability to detect potential introductions of this psyllid, which would be harmful to agricultural production. The authors describe the assay and confirmed that it does not amplify the ITS gene of other psyllids. My major concern for the manuscript is that it is overwritten and over-interpreted. The study is very simple - qPCR assay to detect potato psyllid - yet the text is over 50 pages long, includes unrelated information in the introduction, and includes an overly long discussion. The manuscript should be re-written to focus only on the assay and its use in trade commodities. Specific comments are provided in an attached document. I will apologize for my handwriting.MAJOR POINTSWe appreciate your thorough assessment of our manuscript and thank you for your time. We found your comments very constructive and helpful. We have taken the care to reduce the introduction and discussion sections considerably to provide more focus on the assay and its uses, removing a lot of the duplication. The manuscript has been edited down to 31 pages + supplementary material. We attempted to produce a combined results and discussion section but felt that, due to the technical nature of the paper, keeping these separate was preferable. We hope that you will agree with this assessment on reading the improved version.On the recommendation of the reviewer on line 486 of the previous manuscript we have performed the assay on Potato DNA to check for cross-reaction. No false positives were obtained from 8x reps of 3 Potato samples “Maris Piper” variety. MINOR POINTS1. Line 45: Abstract overwritten, stats to be removed, word count reduced- The abstract Line 21-39 has been reduced in size with all stats removed and is now within the word limit (252 words)2. Line 47: Remove “-“ in “Potato-Psyllids”- Changed to “Potato Psyllid” now line 41 3. Line 49: “The feeding of….” To be changed to “Feeding by”- Changed as suggested now line 434. Line 53: Psyllid yellows refers to the feeding damage described above.- Removed to avoid confusion and improve accuracy. Line 475. Lines 55-56: Change “…is also able to reproduce on…” to “…can also complete development on species of….”- Changed as suggested line 49-506. Lines 56-58: Statement not deemed true- Statement removed line 517. Line 61: Remove statement on Lso transmission to non-host plants of B. cockerelli- Statement removed line 538. Line 64-65: Remove claims about B.cockerelli populations observed to differ in their ability to spread Lso- Changed to: “Evidence suggests that these genetic types may differ in their ability to spread Lso…” Lines 56-579. Line 86: Haplotype B is also found in Bactericera maculipennis- Information added to the text line 7110. Line 111: typo capsicum not italics- Changed to “…Capsicum…” line 8411. Line 223:This table is referenced a lot, make it a real table- Supp Tab. S1 now changed to Table 1. In results section Line 244-250. Cited on lines: 244. Supp Tabs 2-4 renumbered to Supp Tabs 1-3 and Tables 1-3 renumbered to Tables 2-4. 12. Line 276: Submitted to NCBI? Provide accession numbers- Accession numbers added to Table 1. Lines 246-252 and Table 4. Lines 271-27613. Line 314-315: change “….cloned DNA as mentioned below.” To “..DNA below”.- Changed to “….cloned DNA (see below).” Line 29014. Line 319: change “immatures” to “nymphs”- The term “immatures” is preferred by leading psyllid taxonomists Daniel Burckhardt and David Ouvrard, that latter of whom is an author on this paper. See ref: . We have kept the term “immatures” or “immature life stages” throughout.https://doi.org/10.1653/024.097.0132Burckhardt D, Ouvrard D, Queiroz D, Percy D (2014) Psyllid Host-Plants (Hemiptera: Psylloidea): Resolving a Semantic Problem. Florida Entomol 97:242–246 . 15. Line 411: “…Bactericera…” to be italicised- Changed to italics. Line 35416. Lines 439-441: Section to be re-written as inaccurate wording used- This section was removed in the re-write of the discussion. 17. Line 468: Suggestion to perform further validation on Solanaceous DNA- 3 x samples of Solanum tuberosum ‘Maris Piper’ were tested and were negative results added to lines: 194-196 and 284-285. Also results of primer blast etc. did not return any hits for Solanum species or any plant sequences. Reviewer #2- We are thankful to the reviewer for their detailed and careful examination of our paper. They have provided very useful, constructive comments regarding the technical aspects of the paper and have informed us of errors in the finer details. We hope we have incorporated changes to their satisfaction, and we have endeavoured to clear up the technical details that were missing or incorrect. 1. Data availability- Psyllid DNA sequences have been uploaded to GenBank and accession numbers are provided in Tab1. And Tab4; lines 246-252 and 271-276 respectively. 2. Page 8 Line 163: What part of the body is used for micro-dissection to extract DNA? The authors should describe the micro-dissection procedure in more detail rather than only citing the papers.- The non-destructive DNA extraction method is described on lines 121 – 132. “Micro-dissection” was used here to describe the piercing of the abdomen and thorax. “Micro-dissection” has been changed to “pierced” as a more appropriate term (line 126).3. Page 8 Line 172: “For amplification of ITS2 primers CA55p8sFcm-F and CA28sB1d-R [60] and for amplification of CO1 gene regions arthropod barcoding Primers LCO1490 and HCO2198 [61].” The authors should check the grammar here. It is not a complete sentence. It could be “For amplification of ITS2, primers CA55p8sFcm-F and CA28sB1d-R [60] were used, and for amplification of CO1 gene regions, arthropod barcoding Primers LCO1490 and HCO2198 [61] were used.”- Changed as suggested lines 135- 1374. Page 10 Line 204: “DNA was extracted as above using the non-destructive method, amplified and cloned into competent Escherichia coli cells using the TOPO TA cloning kit (Thermo-Fisher).” The authors should specify what genes (ITS2 or CO1?) they amplified for cloning, and what restriction enzyme (EcoRI?) they used to linearize the plasmid.- Information added and moved from later section 2.5.2 Sensitivity. Now line 171-1785. Page 10 Line 212: The authors need to list the real time PCR cycling conditions here, for example XX degrees for XX seconds.- Added lines 178-1816. Page 10 Line 223: “All reactions with non-target psyllid DNA were run in conjunction with a TaqMan Exogenous Internal Positive Control Reagent Kit (Applied Biosystems) to ensure false positives were not obtained due to inhibition within the reaction”. Here, “ensure” should be “rule out the possibility that”- Changed as suggested lines 196-2017. Page 11 Line 226: “DNA from all non-target psyllids was sequenced to ensure psyllid DNA was present in all reactions to rule out false negatives due to inefficient DNA extraction.” What DNA was sequenced? PCR product from ITS2 or CO1? The authors need to specify- Details now added to new Tab 1 and citation to table included on lines 246-2528. Page 11 Line 239: “6 subsequent dilutions were made. Stock DNA 10 ng/μl was linearised using EcoRI restrictions enzyme (New England Biolabs),” Here “6 subsequent dilutions” should be “8 subsequent dilutions”, according to the nine point 10-fold dilution series mentioned on Page 11 Line 236.- Corrected Line 212-2139. Page 12 Line 252: “A six point 1:10 dilution series starting at 10ng/μl was used with each dilution being performed in triplicate.” Here, “six point” should be “nine point” according to Page 11 Line 236.- Only 6 points were used for repeatability. This is sufficient to analyse standard curves between runs. Lines 222-223 refer to sensitivity experiments only.10. Page 12 Line 263: “For each tested parameter, optimization was performed across an eight point 1:10 dilution series starting at 10ng DNA.” Here, “eight point” should be “nine point”, “10ng” should be “10ng/μl”.- Corrected. Line 23411. In Supplementary table S1, green and red color coding should be explained in the text. What does TBC mean? Accession numbers should be given for all the sequences. Accession numbers in Table 3 should also be given and TBC should be explained.- We apologise for this error; this colouring has been removed as was an artefact of preparing the table and shouldn’t have been included in the submitted version. TBC was used to show we were waiting for accession numbers. Accession numbers are now added to tables and TBC removed. Tab. 1 lines: 246-247 Tab.4 lines:12. Page 14 Line 289: “CO1 genes showed higher similarity and generally less conserved and variable regions compared to ITS2 regions.” Here “less conserved and variable” should be “less variable”.- Corrected line 26613. Page 17 Line 310: “0.2 µ/mol” should be “0.2 µM”.- Corrected line 285http://scienceprimer.com/copy-number-calculator-for-realtime-pcr was used.” Here a hyperlink should be created. According to the link and the formula given, 0.00001ng DNA equals 4.879×10000 copies, if length of gene region is considered 187bp . However, the authors calculated that it equals to 200bp. Please double check the calculation.14. Page 18 Line 324: “The copy number calculator available at - Limit of detection is actually 0.000001 ng DNA. This mistake of 10 fold higher amounts stated in the text was found throughout and in tables. We have now corrected them. The correct equation should be:Number of Copies = (ng DNA(0.000001) x 6.022x1023) ÷ ((length of plasmid 4656bp + cloned fragment 700bp) * 1x109 * 660) = 170.36 copy numbers. 15. Page 18 Line 337: “At primer concentration, 0.5 μM the assay was less sensitive only amplifying up to 0.001 ng DNA.” It should be “At primer concentration 0.5 μM, the assay was less sensitive only amplifying up to 0.001 ng DNA.”- Corrected. Lines 313-31416. Page 18 Line 338: “At higher primer concentrations (0.5 and 1.0) the assay showed higher sensitivity” Here “(0.5 and 1.0)” should be “(1.0 μM)”.- Corrected. Line 31417. Page 19 Line 350: “The precision of the assay was lower at higher MgCl2 concentrations 6mM and 8mM (Supp Tab. S3).” Here “6mM and 8mM” should be “7.5mM and 9mM”.- Corrected. Lines 326-32718. Page 19 Line 354: “Reactions at 58 °C were 10 to 100-fold less sensitive than reactions at 58 °C.” Here it should be “Reactions at 58 °C were 10 to 100-fold less sensitive than reactions at 64 °C.”- Corrected. Lines 330-33119. Page 20 Line 367: “We have designed and validated the first species-specific, qualitative real-time PCR TaqMan assay for B. cockerelli by using the comparison of 73 non-target species to identify unique gene regions that were suitable for primer/probe design and species differentiation.” Here “qualitative” should be “quantitative”.- Changed to quantitative. Line 351Reviewer #3- We thank the reviewer for their thoughtful assessment of our manuscript and are pleased that only minor corrections were found throughout. The corrections have improved the manuscript greatly and have ironed out some important technical errors. We hope that our amendments are deemed satisfactory and have covered the issues they have raised.1. Page 8 line 175: please replace amount of primers used with final concentration of primers (or add this)- Added. Line 1382. Page 10 line 213: please add cycling conditions of real time PCR, as done for CO1 and ITS2 amplification- Added lines 178-1813. Table 1: should include also B. cockerelli, so to include fragment size of amplicons for this species. In alternative, fragment sizes can be added to the main text- B. cockerelli added to table 2. Line 262-2634. Table 3: not clear what the "/" symbol in the CO1 column means- Samples with / were not amplified in this region. Accession numbers for each sample have been added and this is explained better in the text. Lines: 252 Tab.1 ; 276 Tab. 45. Page 17 line 310: please check spelling of concentration- Corrected to µM. Line 2856. Page 17 line 316: numbers seem not to add up: how many technical replicates were used per sample?- Information on technical reps is incorporated into table 4. Some samples were tested in duplicate, triplicate or 6x replicates.7. Page 18 line 323: I have tried the formula myself using the concentration (0.00001 ng) and fragment size (187 bp) specified by the authors, but I get a quite different number of ITS2 copies . Please double check, and add actual numbers to the formula.- Limit of detection is actually 0.000001 ng DNA. This mistake of 10-fold higher amounts stated in the text was found throughout and in tables. We have now corrected them. The correct equation should be:Number of Copies = (ng DNA(0.000001) x 6.022x1023) ÷ ((length of plasmid 4656bp + cloned fragment 700bp) * 1x109 * 660) = 170.36 copy numbers. 8. Of some concern is the author's answer to the data accessibility question. Authors stated that they are not going to make all data available, with a generic "Some restrictions will apply". Please explain what data will not be made accessible and why.- All data will be made available. Accession numbers were not available at the time of submission as they were restricted by one or more of our projects until we had consent to upload them to public databases.AttachmentResponse to Reviewers.docxSubmitted filename: Click here for additional data file. 3 Mar 2020PONE-D-19-35047R1A diagnostic real-time PCR assay for the rapid identification of the tomato-potato psyllid, Bactericera cockerelli  and development of a psyllid barcoding database.PLOS ONEDear Dr. Sumner-Kalkun,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.==============================I appreciate the effort you have taken in both addressing the reviewer concerns and revising this work. In that context, I have rendered a decision of minor changes. This is primarily to give you the opportunity to make or address the additional reviewer comments.==============================https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.We would appreciate receiving your revised manuscript by Apr 17 2020 11:59PM. When you are ready to submit your revision, log on to If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocolsTo enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: Please include the following items when submitting your revised manuscript:A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.We look forward to receiving your revised manuscript.Kind regards,Sean Michael Prager, Ph.D.Academic EditorPLOS ONE[Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: (No Response)**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: The revised version of this manuscript is a substantial improvement from the original submission. I have only a handfull of minor suggestions in the attached PDF that the authors might consider.**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool, AttachmentPONE-D-19-35047_R1_reviewer.pdfSubmitted filename: Click here for additional data file. 6 Mar 2020REVIEWER COMMENTS TO AUTHORReviewer #1: The revised version of this manuscript is a substantial improvement from the original submission. I have only a handful of minor suggestions in the attached PDF that the authors might consider.Response:We thank the reviewer for their careful assessment of the manuscript and the comments previously made to help us to improve and streamline the manuscript. We have incorporated most minor changes and edits as detailed below.MINOR POINTSLine 21: Remove “many”- Removed. Line 21 (of document with track changes accepted).Line 24: You can keep central america if you want to, but technically, Central America is a region within North America, so all you really need to say is "North America"- Reduced to just “North America”. Line 24Line 25: add “and is considered an threat for introduction in Europe and other pest-free regions.”- Added: “…; and is considered a threat for introduction in Europe and other pest-free regions.” Lines 24- 25Lines 27-30: remove “successfully” and restructure sentence to remove “(100% n=X)” after each sample type.- Sentence restructured and percentages and sample numbers removed. Lines 27-30.Lines 58-61: I think you need to find a way to combine this short paragraph with the preceding paragraph.- Paragraph added to a previous paragraph. Lines 48-51Lines 67-72: Since the manuscript focusses on potato psyllid, I don't think you need such an in-depth discussion about the various Liberibacter haplotypes- We would prefer to keep the information about Lso haplotypes in as we believe it is an important aspect of Lso epidemiology. The information on Lso haplotypes is greatly reduced compared to the previous manuscripts.Line 77: change “North-West” to “Northwest”- Changed. Line 76Line 108: Change “North-Western” and “South-Western” to “Northwestern” and “Southwestern”.- Changed. Line 107Line 114: US collections of non-targets isn't mentioned in abstract.- Specimens were collected by Andy Jensen from multiple locations in the USA and tested with the assays as detailed in Table 1. We have added “USA” to the abstract. Line 32.Lines 129-132: “DNA extraction in DNeasy Blood and Tissue Kit Protocol from Animal Tissues (Qiagen)” mentioned previously on line 128? - Information condensed to avoid duplication. Lines 128-130AttachmentResponse to Reviewers_v2.docxSubmitted filename: Click here for additional data file. 9 Mar 2020A diagnostic real-time PCR assay for the rapid identification of the tomato-potato psyllid, Bactericera cockerelli  and development of a psyllid barcoding database.PONE-D-19-35047R2Dear Dr. Sumner-Kalkun,We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. 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For more information, please contact With kind regards,Sean Michael Prager, Ph.D.Academic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments: 10 Mar 2020PONE-D-19-35047R2 Bactericera cockerelli  and development of a psyllid barcoding database. A diagnostic real-time PCR assay for the rapid identification of the tomato-potato psyllid, Dear Dr. Sumner-Kalkun:I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. For any other questions or concerns, please email Thank you for submitting your work to PLOS ONE.With kind regards,PLOS ONE Editorial Office Staffon behalf ofDr. Sean Michael Prager Academic EditorPLOS ONE


This cross-sectional study involved 20,606 community-dwelling participants aged ≥ 65 years, residing in New Taipei City, Taiwan. Analytic data included phenotypic frailty, disease burden by Charlson Comorbidity Index (CCI), urban or rural residence, and household income. PM2.5 exposure was calculated from air quality monitoring records, with low exposure defined as the lowest quartile of the study population. 1,080 frail participants (5.2%) were older, predominantly female, had more comorbidities, lived rurally, and had low PM2.5 exposure . In multinomial logistic regression analyses, the likelihood of high PM2.5 exposure was higher in prefrail  and frail adults  than in robust individuals, with stronger associations in those who were male , ≥ 75 years old , non-smokers , had CCI ≥ 2 , and with low household income . This study revealed a significant association between PM2.5 exposure and frailty, with a stronger effect in vulnerable groups.Frailty is common among older people and results in adverse health outcomes. We investigated whether exposure to PM This complex age-related pathophysiology is considerably influenced by combined environmental and genetic factors2.Together with population aging, frailty has garnered considerable interest among clinical researchers and public health professionals, because its reversible and dynamic nature offer promise for disability prevention. Frailty is a geriatric syndrome characterized by declining physiological reserves and increasing vulnerability, in which disrupted homeostasis due to accumulated inter-systemic deficits results in disproportionate health consequences in response to minor stressors3. Accruing epidemiological evidence supports associations between exposure to air pollution and adverse outcomes such as cardiovascular events6, cancer7, Alzheimer’s disease8 and mortality9. Fine particulate matter < 2.5 μm in diameter (PM2.5) is of greatest health concern, not only such small particles can penetrate deeper into the lungs than larger ones do, but also they are likely to be made up of a more toxic mix4.Air pollution is the foremost reversible environmental factor associated with premature death or disability2.5 exposure, include oxidative stress, endothelial dysfunction, and pro-inflammatory effects such as elevated interleukin 6 levels10; frailty shares similar pathoetiology12. Previous studies have investigated potential associations between fine airborne particulates and frailty15. A study of 2059 non-smokers from the United States National Health and Nutrition Examination Survey found a positive association between secondhand tobacco smoke and frailty13. Others confirmed an association between PM2.5 and frailty, measured using a frailty index, among post-myocardial infarction patients who were inherently vulnerable to frailty15. However, it remains unknown whether or not PM2.5 exposure is associated with frailty in the general population. Hence, we investigated associations between annual PM2.5 exposure and frailty among community-dwelling older people, and in potentially vulnerable subgroups.Possible biological mechanisms explaining the health consequences of PM2.5 exposure  for those with prefrail and frailty were 1.4  1.3–1.5) and 1.5 (95% CI 1.2–0.9). Weakness  and low activity  were associated with high PM2.5 exposure, but other phenotypic components of frailty were not  and were also likely associated with PM2.5. Hence, we conducted a sensitive analysis that adjusted for chronic diseases of hypertension, diabetes, heart disease, stroke and chronic kidney disease. Results were similar  and the Taiwan Air Quality-Monitoring Database (TAQMD). The NTCHD was established for early detection of physical conditions and promote senior health. All older adults ≥ 65 years old residing in New Taipei City could receive voluntary government-funded annual examinations face-to-face by physicians, and these examinations include anthropometry, health-related behaviors, physical and mental performance and biochemistry results.22.Upon enrollment, participants gave written informed consent authorizing the New Taipei City Government to process health examination data for research and policy purposes. New Taipei City Department of Health removed all potentially identifying information to protect privacy and generate the anonymized NTCHD. Full details of recruitment and data collections procedures are described elsewhere2.5 exposures.The present study included 26,026 potentially eligible NTCHD participants in 2016. Having excluded 5,420 with incomplete data, the residential areas of the final analytic sample of 20,606 were linked to the locations of TAQMD ambient air-quality monitoring stations to estimate daily PMThis study was designed and conducted in accordance with the principles of the Declaration of Helsinki. New Taipei City Department of Health approved the use of this anonymized dataset for research purposes, and waived the requirement for Institutional Review Board approval. The design and reporting format follow Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.11. Unintentional weight loss is defined as losing > 5% of body weight over the previous 12 months. Exhaustion was determined by affirmation of two questions from the Center for Epidemiologic Studies Depression Scale questionnaire28—‘‘I felt everything I did was an effort’’ and ‘‘I could not get going’’—on ≥ 3 days per week. Physical activity was calculated from the International Physical Activity Questionnaire short-form score, based on self-reported exercise and leisure time physical activities, and expressed as weekly energy expenditure29. Energy expenditure was calculated as the metabolic equivalent relevant to designated type of exercise times body weight and days of exercise. In this study, energy expenditure below 383 kcal/week in men or 270 kcal/week in women was defined as low physical activity according to Cardiovascular Health Study11. Walking speed was measured by a six-metre walk test at a normal pace from a moving start without deceleration. Weakness was defined as maximum dominant handgrip strength of < 26 kg for men or < 18 kg for women, and slowness as 6-m walk speed < 0.8 m/s30.The Cardiovascular Health Study frailty criteria comprise unintentional weight loss, exhaustion, weakness, slowness, and low activity; people with three or more of these frailty phenotypes are classed as frail, those with one or two as prefrail, and those with none as robust31. Urbanicity was dichotomized as urban (level ≤ 3) or rural (level ≥ 4), based on a previous study32.An urbanization index developed by the Taiwan National Health Research Institute was used to determine the urbanization level of each participant’s residential area. This index, which was based on national census data including population density and aging, education levels, medical resources, and agricultural employment, classified 359 regions throughout Taiwan into seven strata from most urbanized (level 1) to the least (level 7)33. Household income data from the Taiwan Ministry of Finance was used as a proxy for socioeconomic status; median annual income equivalent to less than the population median of 19,677 United States Dollars (USD) was considered low.Smoking was defined as using tobacco during the previous 6 months. Charlson Comorbidity Index (CCI) ≥ 2 indicated severe disease burden2.5 level was excerpted from TAQMD. Average annual fine particulate matter concentration was calculated by accumulating daily PM2.5 levels from the 12 months prior to the index interview date; exposure in the lowest quartile (< 16.3 μg/m3) was classed as low.Daily PMAll analyses were performed using SAS statistics software, Version 9.4 for Windows . A two-sided p-value of < 0.05 or 95% confidence interval (CI) that did not include the null hypothesis value were considered statistically significant.2.5 concentrations were transformed logarithmically to approximately linearity assumption for logistic regression. Urbanicity exhibited collinearity with household income, hence income was not included in the statistical model. Univariable and multivariable multinomial logistic regression analyses, adjusted for age, sex, smoking, CCI, and urbanicity, were used to explore associations between frailty status and PM2.5. Multivariable multinomial logistic analysis employed statistical analysis on association between frailty and PM2.5. Frailty as a categorical variable severed as a dependent variable; PM2.5 and other confounders referred as independent variable. The statistical results showed ORs and CI comparing prefrail vs. robust and frail vs. robust, respectively. Log PM2.5 was input to the model after categorizing low/high PM2.5 for sensitivity analysis. Prespecified subgroup analyses included age (< 75 vs. ≥ 75 years), sex , disease burden (CCI < 2 vs. ≥ 2), smoking (no vs. yes), household income  and urbanicity (urbanization index ≤ 3 vs. ≥ 4).The Kolmogorov–Smirnov D test was used to check whether numerical variables were normally distributed. Continuous variables with normal distributions were expressed as means plus/minus standard deviation, and those with non-normal distributions as median . Categorical variables were expressed as frequency/proportions. One-way ANOVA, Kruskal–Wallis Test, chi-square analysis, or Fisher exact test were used as appropriate to compare descriptive characteristics. Cochran-Armitage trend test was used to test for trends. PMSupplementary Information.


The intestinal content was collected for DNA extraction and Illumina sequencing. The PEDV-infected piglets displayed distinct bacterial communities compared to the healthy piglets. PEDV infection decreased the abundance of Shigella and increased the abundance of Lactobacillus, Odoribacter, Anaerovibrio, Helicobacter, unclassified Lachnospiraceae, and Sutterella; affected several functions associated with metabolism, barrier, and immune. NAC supplementation decreased the abundance of unclassified Rikenellaceae and increased the abundance of Lactobacillus, Streptococcus, and Enterococcus in the healthy piglets, decreased the abundance of Oscillospira and Prevotella and increased the abundance of Lactobacillus in the PEDV-infected piglets; altered multiple functions involving in amino acid metabolism, cell signaling, cellular community, disease-related pathways, endocrine, and excretory system. In conclusion, PEDV infection caused severe dysbiosis of gut microbiome, whereas NAC supplementation played a positive role in regulating the gut microbiome during PEDV infection. Therefore, substances that can regulate gut microbiota could be ideal candidates to prevent or treat PEDV infection.This study was to investigate the impact of N-acetylcysteine (NAC) on the gut microbiota in the healthy piglets and the piglets infected with porcine epidemic diarrhea virus (PEDV). Forty seven-day-old piglets were allocated into four groups: control group, NAC group (supplemented with 50 mg/kg body weight NAC), PEDV group (inoculated with 10 Salmonella, Clostridium perfringens, and Escherichia coli, can also be found in healthy mammals  received increasing attention since the large-scale outbreaks in the last decades . PEDV isN-acetylcysteine (NAC) is a source of sulfhydryl groups in cells and scavenger of free radicals as it interacts with reactive oxygen species such as hydroxide and hydrogen peroxide . NAC is The animal use protocol for this research was approved by the Animal Care and Use Committee of Wuhan Polytechnic University (1204-2016-0028). Forty seven-day-old crossbred (Duroc × Landrace × Large White) healthy piglets with 3.17 ± 0.25 kg initial body weight were purchased from a PEDV-negative farm. All piglets were randomly allocated into one of four treatment groups . All piglets were housed in clean pens with strict control of cross-infection. A commercial milk replacer  formulated to meet the nutrition requirement for suckling piglets, was used as the basal diet during the trial. Prior to feeding, the milk replacer (powder) was dissolved in warm water (45–55°C) to form a liquid feed (dry matter content of 20%), as described by Wang et al. (4.5 TCID50 (50% tissue culture infectious dose) per piglet was orally inoculated to the piglets in the PEDV and the PEDV + NAC groups, the same volume of sterile saline was inoculated to the piglets in control and NAC groups. On day 12, all piglets were sacrificed to obtain the intestinal content from jejunum, ileum, colon, and cecum. All samples were rapidly frozen in liquid nitrogen and then stored at −80°C until analysis.The entire trial period was 12 days. During day 5–9 of the trial, the piglets in the NAC and the PEDV + NAC groups were orally administered with 50 mg/kg body weight NAC , and the piglets in the other two groups received the same volume of the liquid milk replacer. On day 9 of the trial, PEDV at a dose of 10The bacterial DNA was extracted from the intestinal content using the QIAampDNA Stool Mini Kit  according to the manufacturer's protocol. The extracted DNA was purified by using the QIAamp spin column . Total DNA was quantified by determining the OD 260 nm/OD 280 nm ratio using the NanoDrop®ND-1000A UV-VIS spectrophotometer . The quality of microbial DNA in each sample was evaluated by 1% denatured agarose gel electrophoresis and the quantity of DNA with Picogreen assay. The microbial DNA were normalized with 10 mM Tris buffer (pH 8.5) to 5 ng/ul.The V3-V4 region of the 16S rRNA gene was amplified by two stage polymerase chain reaction (PCR). The first stage of PCR was processed using the HiFi HotStart ReadyMix kit  with the forward primer: 5′-TCGTCGGCAGCG TCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3′ and the reverse primer 5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCT AATCC-3′. The total reaction volume of PCR was 25 μL, containing 12.5 μL of 2 × HotStart ReadyMix Buffer, 0.5 μL of each primer (5 mM) and 10 ng of template DNA. PCR thermocycling conditions were denaturation at 95°C for 3 min (1 cycle), 95°C for 30 s, annealing at 55°C for 30 s, elongation at 72°C for 30 s and a final extension at 72°C for 5 min. The second stage was index PCR. This step attaches dual indices and Illumina sequencing adapters using the Nextera XT Index Kit . The total reaction volume was 50 μL, containing 25 μL of 2 × HotStart ReadyMix Buffer, 5 μL Cleaned PCR product, 5 μL N7 index and 5 μL S5 index primer. PCR thermocycling conditions were 95°C for 3 min (1 cycle), 95°C for 30 s, annealing at 55°C for 30 s, elongation at 72°C for 30 s (8 cycles), and a final extension at 72°C for 5 min. The PCR production was purified with the Agencourt AMPure XP purification system  and the concentration was measured with SpectraMax i3X Multi-mode detection platform . The purified DNA samples were sequenced using Illumina MiSeq platform .post-hoc was used to compare between the groups. The beta diversity (Bray-Curtis Index) was calculated using principal coordinate analysis (PCoA), with further comparison of groups by analysis of similarities (ANOSIM). Dendrograms and colinear relation diagrams were generated using Majorbio Cloud Platform . Relative abundance of operational taxonomic units (OTUs) were compared by one-way analysis of variance (ANOVA) using Majorbio Cloud Platform, with a Turkey's test as post-hoc and p-values adjusted by false discovery rate (FDR). Functional potentials of OTUs were evaluated by KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment using PICRUSt , a heatmap was generated using TBtools (https://github.com/CJ-Chen/TBtools), and the comparison was processed by ANOVA using Majorbio Cloud Platform with a Turkey's test as post-hoc. Significance was set at p < 0.05 for all comparisons.The raw reads were put for quality control after base calling, and then were subjected to pipeline QIIME for OTU picking and taxonomy as described . Alpha dA total of 3,629,889 reads were obtained with an average length of 460.36 bp across all samples, with 3,629,889 reads from jejunum, 4,658,260 reads from ileum, 2,987,358 reads from colon, and 2,936,753 reads from cecum. The good coverage was obtained over 99.9% for all samples, reflecting reliable accuracy of the sequencing.p < 0.05). No significant difference was observed in the colon and cecum.Evenness, diversity, and richness were calculated by Shannon, Simpson, and Chao1 indices, respectively . Comparep = 0.398) (p = 0.002) (p < 0.001) (p < 0.001)  , while d= 0.002) , colon (< 0.001) , and cec< 0.001) . ParticuProteobacteria, Firmicutes, Bacteroidetes, and Fusobacteria, accounting for an average of over 96% of total sequences  in all groups. AC group . ShigellAC group . BacteroAC group . BacteroAC group .Shigella and Lachnospiraceae_g , increased the abundance of Lactobacillus (p < 0.05). No significant difference was observed between the control and the NAC groups as well as between the PEDV and the PEDV+NAC groups. In the ileum, compared to the control group, the NAC group increased the abundance of Lactobacillus, Streptococcus and Enterococcus, the PEDV group increased the abundance of Prevotella and Odoribacter, and the PEDV+NAC group increased the abundance of Lactobacillus (p < 0.05); compared to the PEDV group, the PEDV+NAC group decreased the abundance of Prevotella and increased the abundance of Lactobacillus (p < 0.05). In the colon, compared to the control group, the NAC group decreased the abundance of Rikenellaceae_g and increased the abundance of Acidaminococcus, the PEDV group decreased the abundance of Rikenellaceae_g and increased the abundance of Anaerovibrio, Lachnospiraceae_g, Lachnoclostridium, Helicobacter, and Sutterella (p < 0.05); compared to the PEDV group, the PEDV+NAC group increased the abundance of Allisonella (p < 0.05). In the cecum, compared to the control group, the PEDV group decreased the abundance of Prevotella and increased the abundance of Anaerovibrio, Oscillospira, Lachnospiraceae_g, Helicobacter, Sutterella, and Butyricimonas (p < 0.05); compared to the PEDV group, the PEDV+NAC group decreased the abundance of Oscillospira (p < 0.05).The differences in the percentage of OTU abundance between all groups were summarized in p < 0.05); compared to the NAC group, the PEDV group increased the abundance of pathway “infectious diseases: parasitic” and decreased the abundance of pathway “excretory system” (p < 0.05). In the ileum, compared to the control group, the NAC group increased the abundance of pathways “signaling molecules and interaction” and “cellular community—eukaryotes” (p < 0.05); compared to the NAC group, the PEDV+NAC group decreased the abundance of pathways “cell motility,” “infectious diseases: bacterial” and “excretory system” (p < 0.05). In the colon, compared to the control and the NAC groups, the PEDV and the PEDV+NAC groups increased the abundance of pathways “cell motility,” “infectious diseases: viral,” and “circulatory system” (p < 0.05). In the cecum, compared to the control group, the PEDV group also increased the abundance of pathways “xenobiotics biodegradation and metabolism,” “cellular community—prokaryotes,” “cellular community—eukaryotes,” and “cancers: specific types” (p < 0.05); compared to the control and the NAC groups, the PEDV group increased the abundance of pathways “signal transduction,” “membrane transport,” “signaling molecules and interaction,” “cell motility,” “infectious diseases: bacterial,” “infectious diseases: viral,” “environmental adaptation,” and “circulatory system” (p < 0.05); compared the PEDV group, the PEDV+NAC group decreased the abundance of pathways “amino acid metabolism,” “signaling molecules and interaction,” “cellular community—eukaryotes,” “cancer—overview,” “drug resistance—antineoplastic,” “endocrine and metabolic diseases,” “cancers: specific types,” “endocrine system”, and “excretory system” (p < 0.05).Functional potentials of the microbiome profile were evaluated by KEGG pathway enrichment, the relative abundance of 25 pathways was found with significant differences between groups . In the Shigella, Enterococcus, and Fusobacterium) and the decreased abundance of short-chain fatty acid (SCFA)-producing bacteria . However, for the first time this study investigated the effect of a potential anti-PEDV substance on the gut microbiota in piglets, NAC was supplemented to the diet of both the healthy and PEDV-infected piglets. Our previous study indicated that NAC improved mucosal structure and intestinal permeability, reduced oxidative stress, and modulated the expression of genes associated with intestinal immune in the piglets during PEDV infection 17). InteBacteroidetes and a higher abundance of Proteobacteria, Firmicutes, and Fusobacteria than the control and the NAC groups in the colon and cecum. The phylum Bacteroides is important for carbohydrate fermentation and polysaccharide catabolism, as well as amino acid and protein utilization , resulted in functional changes associated with metabolism, barrier and immune. However, NAC supplementation played a positive role in regulating the gut microbiome during PEDV infection, as indicated by the altered bacterial populations (decreased Oscillospira and Prevotella and increased Lactobacillus) and function potentials . Therefore, regulating the gut microbiome by anti-PEDV substances or compounds could be taken as a promising candidate for the prevention or treatment of PEDV infection.This study evaluated the effect of dietary supplementation with NAC on the gut microbiome in the healthy and PEDV-infected piglets. PEDV infection caused severe dysbiosis of gut microbiome, as demonstrated by the community variation (beta diversity) and the composition shifts (decreased www.majorbio.com). The datasets generated for this study are available on request to the corresponding author.The original contributions presented in the study are deposited in the Majorbio Cloud Platform database (The animal study was reviewed and approved by Animal Care and Use Committee of Wuhan Polytechnic University.TW and YH planned the project and designed the experiments. TW, YL, and XL conducted the experiments. YL carried out the data analysis. MW, KY, SL, and CJ contributed the animal trials. XL and DZ contributed reagents preparation and samples collection. YL and TW wrote the manuscript and reviewed by QZ, YZ, and DY. All authors have read and agreed to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Hirvonen K, Bai Y, Headey D, Masters WA. Affordability of the EAT–Lancet reference diet: a global analysis. Lancet Glob Health 8: e59–66—2020; In this Article, labelling of units in Table 1 column 1 for serving and kcal per day of dark green vegetables has been corrected. This correction has been made as of Nov 18, 2020.