Whole genome sequencing has become fast, accurate, and cheap, paving the way towards the large-scale collection and processing of human genome data. Unfortunately, this dawning genome era does not only promise tremendous advances in biomedical research but also causes unprecedented privacy risks for the many. Handling storage and processing of large genome datasets through cloud services greatly aggravates these concerns. Current research efforts thus investigate the use of strong cryptographic methods and protocols to implement privacy-preserving genomic computations.Fhe-Bloom and Phe-Bloom, two efficient approaches for genetic disease testing using homomorphically encrypted Bloom filters. Both approaches allow the data owner to securely outsource storage and computation to an untrusted cloud. Fhe-Bloom is fully secure in the semi-honest model while Phe-Bloom slightly relaxes security guarantees in a trade-off for highly improved performance.We propose Phe-Bloom is faster by at least three orders of magnitude. For example, testing disease susceptibility of 50 patients with 100000 variations requires only a total of 308.31 s (σ=8.73 s) with our first approach and a mere 0.07 s (σ=0.00 s) with the second. We additionally discuss security guarantees of both approaches and their limitations as well as possible extensions towards more complex query types, e.g., fuzzy or range queries.We implement and evaluate both approaches on a large dataset of up to 50 patient genomes each with up to 1000000 variations (single nucleotide polymorphisms). For both implementations, overheads scale linearly in the number of patients and variations, while Fhe-Bloom, realizes a comprehensive outsourcing to the cloud, while the partially homomorphic scheme, Phe-Bloom, trades a slight relaxation of security guarantees against performance improvements by at least three orders of magnitude.Both approaches handle practical problem sizes efficiently and are easily parallelized to scale with the elastic resources available in the cloud. The fully homomorphic scheme,  Recent technology advances have made Whole genome sequencing (WGS) fast, accurate, and affordable. Enabled by WGS, several public initiatives –3 have bOn the other side, the genome era also brings unprecedented risks for personal privacy. Genomic information uniquely identifies its owner  and may These significant personal privacy risks are aggravated by various attacks that have proved traditional anonymization mechanisms ineffective for genome data : Wang etSecure collaboration: two or multiple parties collaborate on their joint data, yet without disclosing their individual datasets. ii) Secure outsourcing: one or more parties outsource storage and processing of genome data to an untrusted computation cloud which remains oblivious of the data and computed analyses. In these settings, privacy-preserving variants have been proposed for, e.g., GWAS [In response to the failure of traditional methods to protect genomic privacy, current research focuses on secure computation techniques to protect genomic privacy , 17. Secg., GWAS –20, sequg., GWAS , 20, seqg., GWAS , 22, andg., GWAS , 24.The applicability of secure computation techniques is, however, limited by their significant processing, communication, and storage overheads. Scalability issues are exacerbated by the typically huge amounts of data in genomics. Secure computations and related cryptographic techniques are thus not the panacea to genomic privacy risks. Instead, their limitations and potential must be further explored and the achieved progress must be made available to non-experts. To this end, the center for integrating data for analysis, anonymization and SHaring (iDASH)  organizeBLoom filter based Outsourced Oblivious Matchings (BLOOM), our solution to the 2016 iDASH Secure Genome Analysis Competition. In Track 3 of this competition, participants were challenged to securely outsource the computations for matching a query against a database of patients’ SNPs to the cloud, e.g., to test disease susceptibility of a patient. Our key idea is to represent the query and the patient database efficiently using Bloom filters. The data owner then encrypts the Bloom filters bitwise using packing and stores the encrypted Bloom filters securely in the cloud. To enable computations on these encrypted Bloom filters, we use two different encryption schemes. In our first approach, FHE-BLOOM, we use Fully homomorphic encryption (FHE) which enables the cloud to compute a match under encryption by multiplying query and patients’ Bloom filters and to aggregate the results into single ciphertexts that are returned to the data owner. The core idea of our second approach, PHE-BLOOM, is to construct the query Bloom filter using keyed hashing which obsoletes encryption and enables efficient use of Partially homomorphic encryption (PHE). Note that this scheme slightly leaks access patterns, e.g., the cloud may learn when a query is posed twice. However, the actual contents of a query and, importantly, the patients’ data are still fully protected. PHE thus requires only a slight relaxation of the specified security requirements. We implement, evaluate, and compare both approaches on a real-world data set. FHE-BLOOM performs a disease susceptibility test on a database with 50 patients with up to 100000 variations in approximately 5 min. PHE-BLOOM notably decreases this by four orders of magnitude to 75 ms. FHE-BLOOM was ranked runner-up in the 2016 iDASH competition, while PHE-BLOOM was developed after the competition.In this paper, we introduce Before we present our two solutions, we first concisely define the problem scenario of Track 3 of the iDASH competition and briefly introduce the basic building blocks for our approaches and analyze relevant related work.The iDASH Secure Genome Analysis Competition is organized yearly by the iDASH National Center for Biomedical Computing with the goal to assess and advance the state of the art of research in cryptographic techniques for the protection of genomic privacy , 27. Then patient records. Each record comprises up to m SNPs given in Variant call format (VCF). The researcher also holds a query Q of different SNPs and wants to obtain a list of those patients that match all SNPs in the query. As the data owner is not capable of analyzing the data locally due to limited computation and storage resources, she strives to outsource computations and storage to the cloud. Due to the sensitive nature of genomic data, the cloud must remain oblivious of the computations and stored data. In this setting, the competition goal is to design a secure protocol using Homomorphic encryption (HE) that accurately and efficiently outsources computations and storage to a single cloud server. Importantly, we require a single-round protocol, i.e., after an initial setup phase the data owner poses the query and receives back the result without any intermediate interaction with the cloud server. In the following, we present the detailed requirements for solutions to this problem.Figure Accuracy requirements. The researcher aims to find exact matches, i.e., a patient matches the query iff all queried SNPs are contained in his patient record. The final result is a binary vector that indicates for each patient whether the query matches or not. Moreover, solutions are also judged by their ability to be generalized, e.g., to fuzzy queries or partial matches.n=50 patients and queries of |Q|≤5 SNPs [Performance requirements. The main optimization criterion is the query completion time which includes i) preprocessing and encryption by the researcher, ii) computations on the encrypted data in the cloud, and iii) postprocessing the final results by the researcher. Communication and processing overheads of Step iii) are tightly limited to 20 SNPs and 100 comparisons, respectively, for a database of |≤5 SNPs . CommuniSecurity requirements. Solutions must be secure in the semi-honest adversary model. All cryptographic primitives must offer at least 80 bits symmetric security or equivalent. The cloud must remain completely oblivious of the outsourced data and the results of the query. In particular, the length of the results must not leak the number of found matches. Furthermore, no access patterns should be leaked. The latter requirement was judged qualitatively and could be relaxed.Both our solutions use Bloom filters  to efficB∈{0,1}l of length l with all bits bi∈B set to zero. Before inserting elements, we fix k distinct hash functions B. To add an element B, we compute positions i1=H1(e),…,ik=Hk(e) and set the corresponding bits e∈B, we check whether the bits at all k positions H1(e),…,Hk(e) are set. Due to hash collisions, membership checks can produce false positives, but not false negatives. The false positive probability p is determined by the number of hash functions k, the number of added elements m, and the length l of the Bloom filter. Given a fixed m, setting l=−m log(p)/ log(2)2 and k=− log(p)/ log(2) minimizes the false positive probability Formally, an empty Bloom filter is a bit array sk. This prevents any party not in possession of the key sk to check set membership which is crucial for the security of our second approach. Keyed hashing does not affect the false positive rate and related parameters.In our second solution, we use keyed hashing when adding elements to Bloom filters, i.e., the input element to the hash functions is extended by a secret key In our approach, we encrypt the bits of Bloom filters using HE which allows performing certain arithmetic operations over ciphertexts in the encrypted domain. We utilize this property to securely match a query against the patient records under encryption such that the cloud remains completely oblivious of the processed genomic data. We distinguish three flavors of HE: i) PHE, ii) Somewhat homomorphic encryption (SWHE), and iii) FHE.E(x+y)=E(x)E(y), while ElGamal [E(x·y)=E(x)E(y). Unfortunately, these schemes do not allow the second arithmetic operation which either limits them to simple applications or requires interaction with the data owner for more complex computations.PHE schemes allow us to compute a single arithmetic operation, addition or multiplication, on ciphertexts. E.g., the Paillier  scheme s ElGamal  allows mSWHE schemes  allow adFHE schemes –35 allowIn this work, we present two solutions to securely outsource genetic disease testing, one based on the partially homomorphic Paillier scheme  and one cryptographic protection for computations over genomic data. Architectural or policy-based approaches [From a technical perspective, our work is related to the Private set intersection (PSI) problem which has been widely studied in the literature. We discuss the proposed solutions with respect to the special requirements in our problem setting, i.e., outsourcing to a single cloud server. The broader scope of our work is secure (outsourced) genome analysis and we conclude with a discussion of other use cases in this field. Due to the context of our work, we specifically focus our discussion of related work on proaches , 37 are Private set intersection. In the standard PSI setting, client and server each hold one set of elements and they aim to compute their intersection or its cardinality securely, i.e., without either party learning the other party’s private input. PSI is an important building block for privacy-preserving protocols. Approaches range from (insecure) naive hashing [ hashing  and semi hashing  over pub hashing , 41 to t hashing . Our app hashing .interactively by two or more participants. Indeed, for some of these approaches, the majority of computations could be outsourced to two non-colluding computation peers. This has been shown for Garbled Circuits [single peer and are thus inapplicable to our problem scenario. Relaxing this requirement renders these works interesting alternatives and, generally, opens up the solution space to a wide variety of existing secure computation frameworks and techniques [Most solutions to PSI are realized as two- or multi-party computation protocols, i.e., the result is computed Circuits , BooleanCircuits , 44, andCircuits , 46. ConCircuits , the autCircuits  to two uchniques , 49.In contrast, the protocols by Kerschbaum  and AtalSecure genome analysis. In the related literature, many privacy-preserving variants of applications with a genomics context have been proposed. Their focus has been on GWAS [ on GWAS , 54–56,  on GWAS , 20, seq on GWAS , 22, and on GWAS , 24, 57. on GWAS , 54, 56  on GWAS , 24, 55 FHE-BLOOM and PHE-BLOOM, to Track 3 of the 2016 iDASH challenge which targets secure outsourced genetic disease testing. Our core idea is to efficiently represent the SNPs in the patient database and in the query using Bloom filters and then to reduce the matching steps to operations over sets. We then design two different matching algorithms using either fully or partially homomorphic encryption. The first approach, FHE-BLOOM, facilitates a fully secure and reasonably efficient outsourcing. This solution finished runner-up in the iDASH 2016 challenge. The second approach, PHE-BLOOM, slightly relaxes security guarantees and thereby improves performance by orders of magnitude. This solution was developed after the competition and has not been ranked. In the remainder of this section, we first present a generic overview of both approaches and then explain each one in detail.In this section, we present our two approaches, Overview. Figure preprocessing phase (upper part) during which the patient database is encoded, encrypted, and uploaded to the cloud and an online phase (lower part) that comprises all steps required to process a query. On the highest level, our goals are i) to securely outsource as much processing as possible from the data owner (left) to the cloud (right) and ii) to minimize online overheads. Both approaches proceed in the following steps: At the beginning of the preprocessing phase, the data owner holds a patient database. She creates one empty Bloom filter per patient (using keyed-hashing in PHE-BLOOM) and inserts the patient’s SNPs (Step 1). The data owner then encrypts the resulting Bloom filters bitwise before she uploads and stores them securely in the cloud (Step 2). At the beginning of the online phase, the data owner holds a fresh query to be matched against the database. In FHE-BLOOM, she transforms the query into a Bloom filter, then encrypts and uploads it to the cloud. In PHE-BLOOM, the Bloom filter is built using keyed hashing which allows to upload it to the cloud without encryption. The cloud service then matches query and patient records (Step 3) and aggregates the results in the encrypted domain (Step 4). Steps 3 and 4 are realized differently in our two approaches drawing on the different homomorphic properties of the employed HE schemes. In both approaches, the result vector contains the encrypted number of intersections between the Bloom filters encoding the query and the patient’s record. In the final step, the data owner downloads and decrypts the result vector (Step 5) and checks in a simple postprocessing step whether the number of intersections between the query and patient record is equal to the set bits in the query Bloom filter (Step 6). Note that this check finds all correct matches but may produce false matches with a probability that is upper-bounded by the configurable false positive probability of the underlying Bloom filters.FHE-BLOOM, is to represent patient records and queries as Bloom filters and then match and aggregate them in the encrypted domain using arithmetic operations over the Bloom filter bits. Note that this involves both multiplication (matching) and addition (aggregation) over ciphertexts which requires a fully homomorphic encryption scheme. In the following, we give the detailed steps of our first approach, FHE-BLOOM.The core idea of our first approach, Step 1: Bloom filter encoding. In the first step, the data owner encodes the whole patient database row-wise as Bloom filters. To this end, the data owner chooses k hash functions H1,…,Hk and determines the Bloom filter length l according to the desired false positive probability p and the number m of SNPs that have to be inserted. Note that the choice of hash functions and the Bloom filter length remain fixed for all subsequent steps. The data owner allocates one empty Bloom filter Bi of length l for each patient Pi=1…n. To insert an SNP into a Bloom filter, we first compute a unique and stable representation from the mandatory columns in VCF files to abstract from different VCF versions. We then proceed to insert Pi’s SNPs into Bi by hashing each SNP k times and setting the corresponding bits in Bi, i.e., Q. Additionally, the data owner counts the number of set bits cntQ in the Bloom filter Q. Note that for queries with |Q| SNPs, the Bloom filter Q will have at most cntQ≤|Q|·k bits set.Later, in the online phase, the data owner applies the same steps to her query to obtain the Bloom filter encoding Step 2: Encryption and upload. In the second step, the data owner chooses an FHE scheme, generates a key pair, and encrypts the bits in each Bloom filter. Current FHE schemes support packing techniques which offer multiple plaintext slots within a single ciphertext and allow operating on the encrypted plaintexts in a SIMD manner [sF plaintexts by . We apply packing to the Bloom filter representations of the rows of the database, i.e., we encrypt Bi by ⌈l/sF⌉ ciphertexts  The total n·⌈l/sF⌉ ciphertexts that encrypt the whole database are uploaded and stored in the cloud. In the online phase, the data owner repeats the same steps for her query Q and obtains ⌈l/sF⌉ ciphertexts D manner –60. In tStep 3: Encrypted matching. In the third step, the cloud filters the encrypted patient database according to the SNPs in the encrypted query. This is achieved by multiplying the encrypted Bloom filters Bi and Q component-wise, i.e.,  where ⊙ denotes the encrypted multiplication operation of the FHE scheme. Note that we slightly abuse notation here, since this step actually requires ⌈l/sF⌉ parallel ciphertext multiplications, each of which carries out sF pairwise multiplications in an SIMD fashion. The resulting ciphertexts  correspond to an encrypted Bloom filter in which exactly those bits are set that correspond to the intersection of Q and Bi, i.e., ri,j=bi,j·qj ∀i=1…n, j=1…l.Step 4: Encrypted aggregation. After Step 3, we are left with as many ciphertexts as required to store the whole patient database, i.e., a total of n·⌈l/sF⌉ ciphertexts. Before providing the results to the client, we aim to aggregate them further to reduce communication overheads and postprocessing. Aggregation is performed by summing up all ⌈l/sF⌉ ciphertexts used to encrypt one row into a single ciphertext. To avoid overflows, key parameters must thus be chosen such that each slot has at least log2(|Q|·k) bits.Step 5: Download and decryption. After the cloud has aggregated the results, the data owner downloads and decrypts the n corresponding ciphertexts. The results i and the query Q.Step 6: Postprocessing. The data owner determines all exact matches by comparing the counts ri to the number cntQ of set bits in the query bloom filter. If ri=cntQ, then query Q fully matches patient Pi except for possibly false positives. A single false positive occurs with probability p. Thus, a query Q will produce a false match to a patient with all but one of the queried SNPs with probability p. Generally, if the patient matches only i<|Q| SNPs of the query, the probability of a false match decreases to pQ|−i|.PHE-BLOOM, we represent records and queries as Bloom filters as before. However, we now use a pre-image resistant keyed hash function to insert elements into Bloom filters. The query Bloom filter is then sent to the cloud without encryption since the keyed hashing already protects its contents. This enables a simpler matching algorithm as well as a higher degree of aggregation before results are sent back to the client. Note that the use of keyed hashing prevents the cloud from learning which SNPs are queried. However, the cloud learns when the same query is posed twice. While this presents a slight leakage of access patterns, performance is increased by orders of magnitude. Importantly, the patient database is still fully protected through encryption. We now explain each step of PHE-BLOOM in detail.In our second approach, Step 1: Bloom filter encoding. Step 1 of PHE-BLOOM is similar to FHE-BLOOM with the only difference that the data owner uses keyed hashing to insert SNPs into Bloom filters. This prevents anyone who is not in possession of the hashing key from determining which SNPs are contained in a given Bloom filter.Step 2: Encryption and upload. The data owner chooses a PHE scheme, generates a key pair and encrypts the bits in each Bloom filter. In contrast to our first approach, we pack Bloom filter bits column-wise into ciphertexts using Horner’s scheme [sP slots, we obtain for the jth column ⌈n/sP⌉ ciphertexts  The resulting total l·⌈n/sP⌉ ciphertexts are uploaded to the cloud. The query is uploaded without encryption, relying on keyed hashing to protect its content.s scheme . With sStep 3: Encrypted matching. Since the cloud obtains the query bits in the clear, matching the query to the database becomes a simple matter of selecting those columns corresponding to set bits in the query, i.e., we select the encrypted column jiffqj=1. We thus retain at most |Q|·k encrypted columns.Step 4: Encrypted summation. Before providing the results to the client, the cloud aggregates them to reduce communication and postprocessing overheads. Aggregation is done by summing up columns element-wise which is realized using encrypted additions and reduces the result’s size to only ⌈n/sP⌉ ciphertexts.Step 5: Download and decryption. The data owner downloads the ⌈n/sP⌉ encrypted results from the cloud. After reception, she decrypts and unpacks them to obtain the counts Step 6: Postprocessing. The occurrence of matches is decided as before by comparing the counts ri to the number cntQ of set bits in the query Bloom filter. The probability for a false positive is exactly the same as for FHE-BLOOM.FHE-BLOOM is based on FHE which affords full security and competitive performance with the other solutions presented at the iDASH workshop. In comparison, PHE-BLOOM provides slightly weaker security guarantees but requires only PHE which significantly decreases overheads.In summary, both our approaches are based on the idea of reducing the given disease testing problem to set operations. We then identify Bloom filters as an efficient data structure that allows manipulating sets efficiently in the encrypted domain using SIMD arithmetic operations on the individual bits of the Bloom filter. Here, FHE-BLOOM and PHE-BLOOM. We first formally analyze runtime and communication complexity  includes all steps required for pre-processing, encryption, and upload of the patient database; ii) Query (Cloud) comprises all computations by the cloud over encrypted data per query; iii) Query (Client) includes preparation, encryption, and upload of the query as well as download, decryption, and postprocessing of the result. For simplicity, we measure runtime complexity in terms of the number of encryptions and decryptions as well as additions and multiplications in the encrypted domain. In comparison, (keyed) hashing causes only negligible overheads that are omitted in our complexity analysis. Communication complexity is measured in the number of exchanged ciphertexts.We compare the runtime and communication complexity of both approaches in Table DB Setup: The setup overheads for both approaches scale linearly in the number of patients n and length of the Bloom filter l. Both approaches support SIMD operations which decrease complexity by a factor 1/s, with sF and sP denoting the number of slots of the FHE and PHE schemes, respectively. The exact values of sF and sP depend on the chosen key, e.g., sF=1180 and sP=170 in our evaluation.Query (Cloud):FHE-BLOOM requires the cloud to perform PHE-BLOOM requires only Query (Client): For FHE-BLOOM, the online processing and communication overhead per query for the client are in PHE-BLOOM notably decreases the online overheads for the client by orders of magnitude to PHE-BLOOM are made possible by slightly relaxing security guarantees. While a small leakage of access patterns must be tolerated, PHE-BLOOM still fully protects the patient data stored in the cloud.FHE-BLOOM and PHE-BLOOM. We deliberately analyze and compare only our own two approaches. A comparison of FHE-BLOOM with the competitors’ approaches has been presented by the organizers of the iDASH challenge [We first describe our implementations and the experimental setup, before presenting our quantitative evaluation of runtime, communication, and memory overhead of hallenge . We alsoImplementation.FHE-BLOOM is implemented in C++ based on HElib [on HElib , 63. AllPHE-BLOOM is implemented in Python and uses our own implementation of the Paillier scheme [PHE-BLOOM manages to keep all data in memory for the problem sizes in our evaluation. However, chunk-wise processing of the patient database as in FHE-BLOOM is also straightforward to implement for this approach if memory consumption needs to be reduced. Both implementations use the pybloom implementation of Bloom filters which uses SHA512 as hash function. For keyed hashing, we append a secret key to the hashed input just as done for salted hashes. Both implementations are available online to facilitate reproducibility of our results [r scheme , 64 and  results .Experimental setup. We perform experiments on a desktop client  and a server  that communicate over a Gigabit LAN. As in the competition, we limit execution on both machines to 4 cores. All cryptographic primitives are configured to offer at least 80 bit symmetric security.n, maximum number of SNPs per patient m, and false positive probability p. If not stated otherwise, we fix n=10,m=100000, and p=2−14. The setup overheads are measured over 5 independent runs and online overheads over 30 independent runs. We report the mean and the standard deviation.We use the dataset provided by the organizers of the iDASH competition and vary the parameters that determine the performance of our approach, i.e., number of patients n, m, and p the performance of our approach does not in any way depend on which or how many SNPs are queried and whether they match or not.Since the provided dataset contains no queries, we use random matching and non-matching queries in our evaluation. However, we emphasize that for fixed FHE-BLOOM are lower for small n but grow quickly, while PHE-BLOOM has a higher overhead first but, interestingly, does not increase when moving from n=1 in Test 1 and 2 to n=50 in Test 3. This is due to the different packing strategy of PHE-BLOOM that packs column-wise with sP=170 slots which is easily big enough to fit each column into a single ciphertext. To draw a fair comparison between both approaches, we measure the asymptotic runtime per patient for fixed m=100000. FHE-BLOOM then requires 27.98 s (σ=2.39 s) per patient in the database, while PHE-BLOOM only requires 5.40 s (σ=0.12 s). While these overheads are significant, they are still reasonable and are computed only once. We now focus on the main optimization goal, i.e., the online runtime per query.Table FHE-BLOOM, the query runtime increases linearly in n and m and is in the order of seconds for Test 1 and 2 and in the order of minutes for Test 3. In contrast, the online overheads of PHE-BLOOM are smaller by three orders of magnitude. Figures n, m, and p. The plots show mean and standard deviation for i) query preparation on the client, ii) query upload, iii) processing the encrypted data in the cloud, iv) results download, and v) postprocessing the results.For FHE-BLOOM, we observe linear growth in the number of patients n  per patient during setup of the database and a fixed 265.29 MB (σ=0.00 MB) per query irrespective of n, while downloading only 0.45 MB (σ=0.00 MB) per patient in the database. In contrast, PHE-BLOOM asymptotically only uploads 3.13 MB (σ=0.00 MB) per patient during setup and 0.25 MB (σ=0.00 MB) per query while needing to download only 1.58 B (σ=0.00 B) per patient. Thus, communication overheads in PHE-BLOOM are two orders of magnitude smaller than in FHE-BLOOM for large patient databases.Table m=100000 and n=50. For both approaches, the client’s memory consumption in both phases is fairly low with a maximum consumption of 156.86 MB (σ=1.78 MB) and 143.85 MB (σ=0.38 MB) in FHE-BLOOM and PHE-BLOOM, respectively. Clearly, these overheads are manageable even by constrained clients. For FHE-BLOOM, the cloud’s memory consumption is fairly low as well and amounts to only 92.97 MB (σ=0.15 MB). This is achieved by storing the encrypted database on disk and reading and processing it in chunks of the desired size. While this introduces perceivable I/O overhead, it becomes necessary for the larger problem settings, e.g., in Test 3 where the encrypted database has a storage size of 13264.54 MB (σ=0.01 MB) and is too big to be kept in the memory. In contrast, the encrypted database in our second approach, PHE-BLOOM, is at least one order of magnitude smaller and can be kept in memory entirely. While this saves I/O overhead, it increases memory consumption to 2081.70 MB (σ=0.03 MB). In scenarios where the cloud has constrained memory, the database could also be processed chunk-wise to reduce memory overhead, similarly to our implementation of FHE-BLOOM. Overall, the cloud’s memory overheads are still feasible in both approaches even for large problem sizes.Table FHE-BLOOM and PHE-BLOOM, w.r.t. their security guarantees and their limitations and potential extensions.In this section, we discuss our two approaches, We briefly discuss security of our approaches in the semi-honest adversary model. In the semi-honest model, all parties correctly follow the protocol but may try to infer additional information from the protocol transcript. The semi-honest model has many applications and advantages: It allows for efficient protocols and protects against insider and outsider attacks in settings where both parties are not actively cheating. In our setting, the cloud does not contribute any private data. Thus, we only have to show that the cloud learns nothing from the protocol transcript about the patient database, the query, and the result.FHE-BLOOM, the client begins by uploading the encrypted database to the cloud. While the cloud learns the number of patients n in the database, we argue that it learns nothing else about the content of the database due to the semantic security of the employed encryption scheme. In particular, semantic security guarantees that the cloud cannot learn any partial information from the ciphertexts, e.g., whether two patients have the same SNPs. Since all encrypted Bloom filters have the same size, the cloud does not even learn the individual number of SNPs per patient but only the configured maximum number m. In the second step, the client poses multiple queries to the cloud. Again due to the semantic security of the encryption scheme, the cloud learns nothing about the queried SNPs and cannot even distinguish whether the same query was posed twice. Thus, no access patterns are leaked. Following, the cloud computes the matching and aggregation steps. All operations in the cloud are performed on encrypted data, hence any intermediate results remain encrypted. Importantly, the matching and aggregation steps always access the complete database and all bits in the query such that data access patterns are completely independent of the database, the query, and the result. We thus argue that the processing steps reveal nothing to the cloud and even withstand timing side-channel attacks. Finally, the cloud returns the encrypted results to the client. The results always consist of n ciphertexts independent of the number of matches found, and hence do not leak information to the cloud. We thus conclude that FHE-BLOOM is fully secure in the semi-honest model and even withstands timing attacks.In PHE-BLOOM, the client begins with the upload of the encrypted database as before. The employed Paillier scheme is semantically secure and thus the previous security arguments apply. Different to FHE-BLOOM, the query is not encrypted in PHE-BLOOM. Instead, we use a pre-image resistant keyed hash function to map SNPs into the query Bloom filter, where only the client knows the hashing key. The use of a secret hashing key prevents the cloud from mounting a brute-force attack to learn which SNPs are queried. Note that we use the key only to salt the hash and do not require, e.g., robustness against length-extension attacks as provided by keyed hash functions for message authentication such as HMAC [PHE-BLOOM is secure in the semi-honest model.In  as HMAC . HoweverPHE-BLOOM shows that tolerating a slight leakage of access patterns leads to significant performance speed-ups. To conclude the security discussion, we briefly point out a different relaxation of the security requirements that can achieve performance improvements. As we have noted in our analysis of related work, a significant part of the research on secure genomic analysis relates to the secure collaboration setting. In this setting, state-of-the-art techniques such as Yao’s Garbled Circuits [strict secure outsourcing setting. Relaxing the strict requirement of outsourcing to a single party, however, renders these established secure multiparty computation techniques applicable in our problem scenario. Instead of outsourcing to a single cloud provider, the data owner would securely split data across two cloud services and instruct them to carry out the genomic computations together using any of the established secure computation techniques. It is important to note that this relaxation introduces the additional security assumption that the two parties do not collude which must be further discussed in the context of genomics.Circuits , the GolCircuits , or secrCircuits , have ofOur evaluation has shown that the most expensive step is the setup of the patient database in both approaches. Although these overheads amortize over multiple queries, we aim for a system that does not require repetition of the whole setup phase each time the database has to be changed or query functionality is extended. We thus first analyze the costs for modifying the encrypted and outsourced patient database at a later point in time, i.e., adding, deleting, and modifying patient records. Afterwards, we briefly discuss the flexibility of our two approaches in answering different types of queries beyond exact matches.Modifying the encrypted database. In FHE-BLOOM, it does not matter whether patient records are uploaded in one batch during setup or whether they are added later on. In both cases, we need to construct one Bloom filter per patient, encrypt, and upload it. The runtime overheads are thus exactly the asymptotic costs per patient during database setup reported earlier. To delete a patient the cloud simply deletes the corresponding ciphertexts. A record can be modified by simply replacing it. In comparison, single row-wise operations, such as adding, deleting, and modifying a patient, are more expensive in PHE-BLOOM. Each of these operations requires the client to create and upload exactly l new encryptions. This is due to the different packing strategy which packs the data of sP patients column-wise into l ciphertexts. However, this allows us to operate on a batch of sP consecutive rows in an SIMD fashion. Thus, operations should be performed on batches of sP patients whenever possible such that overheads amortize. Also, PHE-BLOOM is more efficient for column-wise operations, e.g., adding, deleting, or modifying particular SNPs of the patients.Answering further query types. Both FHE-BLOOM and PHE-BLOOM are designed to compute exact matches. However, the results can also be interpreted as the size of the intersection between query and patient records to probabilistically estimate the degree of a partial match. In particular, this allows answering negative queries efficiently, e.g., which patients do not show certain variations. Note that both approaches allow us to compute arbitrary linear combinations of the patients’ SNPs. This allows us to answer weighted queries, e.g., enabling disease tests where certain SNPs are more critical than others. Concretely, this can be implemented in both approaches by assigning integer weights instead of bits to the Bloom filter slots and interpreting the final results as the weights of the matchings. Finally, with Bloom filters at the core of both approaches, a wide variety of Bloom filter extensions might apply to add support for, e.g., range queries [ queries  or local queries .FHE-BLOOM, uses fully homomorphic encryption to protect the patient database and the posed queries while fully outsourcing storage and computations. In our second approach, PHE-BLOOM, we slightly relax security guarantees by allowing a slight leakage of access patterns. This enables efficient use of partially homomorphic encryption which significantly improves performance while still realizing a comprehensive outsourcing and full protection of patient data. Concretely, FHE-BLOOM queries a database of 50 patients with up to 10000 disease markers in 308.31 s (σ=8.73 s), while PHE-BLOOM performs the same test case over three orders of magnitude faster, in only 0.07 s (σ=0.00 s). Both approaches support flexible and efficient management of the outsourced data, e.g., adding or modifying patient records, and may be extended to support further query types beyond exact matches that were required in the competition. FHE-BLOOM was ranked runner-up in the iDASH competition, while PHE-BLOOM was developed only afterwards but presents an exciting alternative when high performance is of paramount importance.The grave privacy risks and failure of traditional protection schemes make evident the need for strongest possible protection for genomic data. Currently, best protection is achieved by secure computation protocols that share data only in cryptographically protected form such that the data is never learned by third parties in clear. The 2016 Secure Genome Analysis Competition, organized by the iDASH center, aims to assess the state of the art of these techniques and to make them available to non-experts. In this paper, we presented two solutions to Track 3 of this competition, i.e., secure outsourced disease testing. Both of our solutions are based on Bloom filters but differ in the use of homomorphic encryption to realize computations over encrypted data in the cloud. Our first approach,


In Vitro Model of Digestion: Bioaccessibility of Anthocyanins and Carotenoids” [Evidence-Based Complementary and Alternative Medicine has retracted the article titled “The Antioxidant and Starch Hydrolase Inhibitory Activity of Ten Spices in an tenoids” , as the


During a femorofemoral bypass, the heel of a dacron graft may be compressed under the inguinal ligament, with the subsequent risk of occlusion. Furthermore, an additional patch may be required to close larger arteriotomies. The following technique addresses both these difficulties without incising the inguinal ligament. The graft is split into two ‘toes’, instead of a ‘heel’ and a ‘toe’. The inguinal ligament now lies over the superior toe of the graft instead of compressing the heel of the graft. The toes can be lengthened if the arteriotomy is extended into the profunda femoris, avoiding the need for a patch.


Objective: Recipient vessel caliber may be the single most important variable for flow to free tissue transfer. We performed cadaveric dissection of the external carotid artery and its branches to analyze average diameter in order to determine an algorithm for recipient vessel selection in head and neck reconstruction. Methods: The external carotid artery and branches were exposed on 3 lightly embalmed male human cadavers, aged 82 to 85 years. Each vessel was dissected, and luminal diameters were recorded with calipers. Results: The proximal ECA had the greatest average diameter (4 ± 0.6 mm) and potential flow; followed by distal ECA (2.85 ± 0.4 mm) facial (2.0 ± 0.6 mm), lingual (1.65 ± 0.6 mm), superior thyroid (1 ± 0.3  mm), and superficial temporal (0.85 ± 0.4 mm). There was a trend towards size variation between sides of the same cadaver. Conclusion: The external carotid artery has the greatest internal diameter and potential blood flow. It should be considered, when feasible, especially for defects of the upper third of the head. For defects of the lower third, the facial artery and the lingual artery should be utilized before the smaller diameter superior thyroid artery. Vessel selection is more challenging in the setting of radiation therapy, complex trauma, and prior neck surgery. In these settings, it is useful to have knowledge of the vascular anatomy and an objective algorithm for recipient vessel selection. None haThe ECA and all branches were present in all 3 cadaveric specimens. No significant luminal atherosclerosis was found. The internal diameter of the proximal ECA, distal ECA, superior thyroid artery, lingual artery, facial artery, and superficial temporal artery  had aver-8,Microvascular free tissue transfer is a useful option in the armamentarium for reconstruction of head and neck defects. It is technically challenging, but success rates are high.9The physiologic relationship between vessel size and blood flow is described by Poiseuille's equation . The dom,The ECA had the largest diameter and therefore has the greatest potential blood flow. It should be considered whenever practical, especially for defects in the upper third of the head. The superficial temporal artery can also be considered but should be the second choice due to its significantly smaller diameter. For defects in the lower third of the face, the facial artery is preferred, followed by lingual and superior thyroid arteries. There have been several algorithms for recipient vessel selection published in literature. Other algorithms suggest superficial temporal vessels for upper-third defects and facial or the superior thyroid arteries for defects of lower two-thirds.8,25,8,13,As primary radiation therapy for malignancies of the head and neck and metachronous tumors becomes more commonplace, the choice for most appropriate recipient vessel can become obscured.4The complex vascular anatomy of the head and neck provides many options for recipient vessels. It is important for reconstructive surgeons to be familiar with vascular anatomy of the head and neck, especially the relative size of potential recipient arteries. Selection of venous outflow is also of significance but is beyond the scope of this study. Venae comitantes of the recipient artery, internal jugular, and external jugular are commonly used in an end-to-end or end-to-side fashion. Vein selection warrants further examination in future studies.


A 76 year-old man with a past medical history of type 2 Diabetes, stage 3 chronic kidneydisease and previous multivessel coronary artery bypass surgery 10 years before wasadmitted with an acute coronary syndrome. Coronary angiogram showed an occludedsaphenous vein graft (SVG) to first diagonal. After restoring flow by means of thrombusaspiration, optical coherence tomography (OCT) runs were required. Localized and widelypatent segments of the graft showed a clear three-layer configuration, suggestive of SVGfocal arterialization. Proximally, predominantly red thrombus determined a criticalstenosis and a thin cap fibroatheroma was evident in an arterialized segment of thegraft contiguous to the thrombotic lesion. Conversely, the rest of the SVG kept itsvenous appearance and had three different areas of stenosis .Since the early 70´s, there has been multiple efforts to describe and understand factorsdetermining SVG patency. Remodeling - mainly through intimal hyperplasia and further neoatherosclerosis - is responsible for most of the late graft loss.The present case adds to what is previously known by showing distinct segments ofthree-layered vein graft wall, and also that SVG "arterialization" can be a focal andheterogeneous process throughout the vessel wall. Furthermore, it was a vulnerableplaque from this remodeled segment the one that probably harbored the thromboticcomplication.Given its superior image resolution, OCT can significantly contribute to ourunderstanding of vein graft failures.


This letter addresses a number of discrepancies found in several publications related HMB-FA and ATP supplementation. Our letter concerns the paper from Wilson et al. . At the ClinicalTrials.gov [We focus here on an unexplained inconsistency between these papers –3. Firstials.gov , but difClinicalTrials.gov for this study, which lists only a single placebo group [It is important to make clear that the three papers –3 are rebo group ; 2) In Lbo group  with thebo group –3, whereClinicalTrials.gov [ClinicalTrials.gov [ClinicalTrials.gov [Inconsistent descriptions of control groups between papers. According to the 2013 Wilson et al. article [ials.gov . Furtherials.gov . Finallyials.gov , but thiDiffering number of subjects in control groups between papers. In Wilson et al. , 3 subjeExtraordinary homogeneity between papers. Table


Candidatus Liberibacter asiaticus (Las). Las infection causes yellow shoots and blotchy mottle on leaves and is associated with excessive starch accumulation. However, the mechanisms underlying the starch accumulation remain unknown. We previously showed that the Las5315mp effector induced callose deposition and cell death in Nicotiana benthamiana. In this study, we demonstrated that Las can experimentally infect N. benthamiana via dodder transmission. Furthermore, we revealed another key function of the Las5315 effector by demonstrating that transient expression of the truncated form of the effector, LasΔ5315, induced excessive starch accumulation by 6 fold after 8 dpi in N. benthamiana after removal of the chloroplast transit peptide from the Las5315mp. The induction mechanisms of LasΔ5315 in N. benthamiana were attributed to the up-regulation of ADP-glucose pyrophosphorylase, granule-bound starch synthase, soluble starch synthase, and starch branching enzyme for increasing starch production, and to the significant down-regulation of the starch degradation enzymes: alpha-glucosidase, alpha-amylase, and glycosyl hydrolase for decreasing starch degradation. This is the first report that Las can infect the model plant N. benthamiana. Using this model plant, we demonstrated that the LasΔ5315 effector caused the most prominent HLB symptoms, starch accumulation and chlorosis as Las infection in N. benthamiana. Altogether the Las 5315 effector is critical for Las pathogenesis, and therefore, an important target for interference.Huanglongbing (HLB), a destructive plant bacterial disease, severely impedes worldwide citrus production. HLB is associated with a phloem-limited α-proteobacterium,  Candidatus Liberibacter  and Trioza erytreae (del Guercio) (African citrus psyllid)  is one of the most complex and severe diseases that affects all commercial citrus species. HLB is associated with an unculturable phloem-limited α-proteobacterium d) Bove, . The mosd) Bove, , which id) Bove, . There iCa. Liberibacter asiaticus (Las) is a bacterial plant pathogen with a dual host life cycle dependent on sap-feeding insects for transmission to plants. Pathogens may also manipulate the development of their psyllid hosts to improve growth, enhance colonization, and increase transmission . This effector induces callose deposition and targets the chloroplast. Interestingly, the excessive callose formation in the phloem seems to be linked to a plant defense reaction to Las bacterium. Las infection processes can lead to perturbation of normal carbon partitioning, excessive starch accumulation in plastids, chloroplast disruption, increase of H2O2, insufficient root development, reduced size and aberrant fruit development, and slow growth  was added. For each construct, we infiltrated three leaves of three 4 week-old N. benthamiana plants with the A. tumefaciens suspension. The agro-infiltrated leaves were analyzed for protein localization at 3 dpi under a microscope (Olympus BX51-P) equipped with a UV light source. Agroinfiltrated plants were kept in a greenhouse for the duration of the experiment and observed for phenotypic changes.2 and 10% [w/v] KI) and incubated in water to allow fading until a clear background was obtained. Iodine staining was repeated at least three times for each construct.Starch was visualized by iodine staining reagent (Sigma). Four dpi detached leaves or Las infected leaves were boiled in 95% ethanol to remove leaf pigments thoroughly and then washed twice with deionized water. Rehydrated leaves were stained for 10 min in 5% iodine solution , 1 leaf disc was collected using cork borer number 6 at 2, 4, 6, and 8 dpi from tissue agro-infiltrated with the corresponding constructs. Leaf discs were pulverized using liquid nitrogen and then starch was extracted and digested following the manufacturer's instructions. After the digestion the samples were measured at Ex/Em wavelength 535/587 nm by the LUMIstar microplate reader (BMG Labtech). Three biological replicates were used for the analyses.Detached leaves were rinsed with distilled water and blotted dry. Leaves were sliced with a razor blade into 1- to 2-mm strips and placed in 20 ml of filter-sterilized Enzyme Solution . Plant tissue was shaken at 35 rpm in the dark at room temperature for 16–18 h. Protoplasts were collected by sieving through 8 layers of cheesecloth and centrifuged for 7 min at 100 g. Supernatant was removed, and the pellet was used for iodine staining and microscope analysis.N. benthamiana leaves at 4 dpi using a 6 mm cork borer; leaf discs were ground in liquid nitrogen and suspended in extraction buffer plus protease inhibitor cocktail as per the manufacturer's protocol (denaturing). Proteins were separated by SDS-PAGE 4–12% acrylamide gel and electro-blotted to a nitrocellulose membrane using an iBlot blotting system (Life Technologies). The membrane was blocked with TBS-T containing 5% skimmed milk powder for 1 h at room temperature.Two leaf discs were collected from the infiltrated part of For immunoblot analysis, antibodies for LasΔ5315 were generated against a peptide sequence of LasΔ5315 (CISRTRIDSSPPPHG) (GenScript) and then HRP conjugated using Lighting-Link HRP kit (Innova Bioscience). The membrane was first incubated with primary antibody for 1 h with mild agitation and then washed 3 × 10 min; protein band was detected and analyzed using WestenSure Chemiluminescence substrate and the digital imaging system C-DiGit® Blot Scanner (LI-COR).665–5.76 · A649 used − 7.60 · A665 + 25.8 · A649  and immediately before onset of the photoperiod (night). Sample leaves were quickly frozen in liquid nitrogen and ground to a powder using an autoclaved mortar and pestle. Total RNA was extracted using TRIzol Reagent (Invitrogen). Total RNA concentration and purity were determined from the ratio of absorbance readings at 260 and 280 nm, using a Nanodrop 1000 spectrophotometer (Thermo Scientific). cDNA synthesis was performed with poly-T primers using the M-MLV reverse transcriptase system (Promega) according to the manufacturer's instructions.Total RNA was extracted from 3 separate agroinfiltrated leaves using 3 −ΔΔCt method was used to calculate relative expression as previously described  reagent and 2 μL of DNA template. The following standard thermal profile was used for all amplifications: 95°C for 5 min, followed by 40 cycles of 95°C for 3 s and 62°C for 30 s. Primer sequences are listed in Table Cuscuta pentagona) germinated on Las-infected Duncan citrus plants was used to inoculate N. benthamiana with Las bacteria. Connections were established on 4 week-old N. benthamiana plants and maintained for 4 weeks, after which the dodder was removed. Control plants were connected with uninfected dodder for the same time period. Plants were kept in a greenhouse.Dodder  as described above.To determine Las bacterial titer, symptomatic and healthy leaves were collected from in vivo once Las5315mp has localized to the chloroplast. Transit peptide directs post-translational localization and is removed upon arrival in the organelle   Figure , yieldin) Figure , and 4 d) Figure ,S3A. In ) Figure ,  Figure . Agroinf) Figure .In order to establish the localization pattern of LasΔ5315, we imaged the leaf epidermal layer of the infiltrated zones and compared to zones infiltrated with the control GFP vector. While the control showed diffuse fluorescence Figures , GFP-tagLasΔ5315 expression in N. benthamiana leaves induced starch accumulation by using iodine staining for starch visualization. We observed massive starch accumulation at 4 days post-infiltration (dpi)  Figure . Agroinf) Figure . In cont) Figure .LasΔ5315 than in tissue expressing GFP at all time points except for 2 dpi daytime. Starch concentrations increased steadily in LasΔ5315-expressing tissue throughout the time course, but stayed relatively constant in tissue expressing GFP, resulting in a 3-fold difference during the day and 5-fold difference during the night at 8 dpi. This led us to hypothesize that in tissue expressing LasΔ5315, starch synthesis enzymes were upregulated, starch degradation enzymes were downregulated, or some combination of the two.To quantify starch accumulation, a fluorometric assay was carried out at 2, 4, 6, and 8 dpi, both at the end . In contrast, transcript levels of the starch degradation enzymes alpha-glucosidase, alpha-amylase, and glycosyl hydrolase . This result suggests that starch accumulation may play a role in chloroplast breakdown, and therefore be associated with chlorosis.Starch over-accumulation and chlorosis are two of the most prominent symptoms of HLB. Chlorosis results from breakdown of the thylakoid membrane, which is thought to result from starch accumulation within the chloroplast  as an artificial host for the bacterium has improved the situation, but genetic tools for use in periwinkle have not yet been developed. In contrast, a wide variety of genetic tools including viral expression vectors, agroinfiltration and extensive studies on plant disease resistance already are available for N. benthamiana (Van Ooijen et al., N. benthamiana. To confirm similar pathology of Las infection in N. benthamiana as in citrus, we analyzed starch accumulation in infected and control N. benthamiana plants following the normal night starch degradation phase. Upon iodine staining, infected leaves showed the same dark-colored phenotype as expression of the LasΔ5315 effector alone, indicating that Las indeed prevents starch degradation during the night, causing starch accumulation. Interestingly, when a single infected N. benthamiana leaf was imaged before and after iodine staining (Figures HLB research has long been hindered by the inability to culture Las  Figures , the darLasΔ5315 showed increased expression of starch synthesis genes and decreased expression of starch degradation genes. Importantly, our data suggest that Las5315 effector protein may be responsible for the dysregulation of starch-related enzyme transcripts, causing starch accumulation and the consequent chlorosis phenotype.Las infected citrus plants accumulate large amounts of starch in the aerial tree parts (Etxeberria et al., N. benthamiana demonstrated a failure to breakdown starch during the night. This is the first study to show a causal relationship between Las effector expression, starch accumulation, and chlorosis, indicating a potential target for novel HLB therapies. It is also the first report of Las transmission to N. benthamiana, which is a suitable and convenient host for studying Las due to its status as a ubiquitous model plant. Our establishment of a N. benthamiana Las-infection model, as well as our identification of a protein target for HLB therapies, represent important progress toward the understanding and elimination of HLB.In conclusion, here we demonstrated that the LasΔ5315 effector induced excessive starch accumulation in plant cells by modulating the transitory starch metabolism, which led to dysfunctional chloroplasts. Evaluation of starch content in Las-infected MP and YD designed the research. MP and VA performed data collection and analysis. MP, VA, and YD interpreted the data and prepared 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.


I am very pleased to announce that with this first issue of the third volume of the Journal of Applied Clinical Medical Physics (JACMP), Karl Prado is joining the Editorial Board as an Associate Editor. He joins John Horton and Mike Herman as an Associate Editor in Radiation Oncology Physics. Both Associate Editors are doing a superb job, but with the increasing number of submissions in radiation oncology physics papers, further help is needed. John Horton will continue to take the prime responsibility for brachytherapy manuscripts, and Karl Prado will help Mike Herman with the external beam papers.Except for the editorial office staff , the Editorial Board volunteers their time and serves without compensation. Take a moment next time you see them or correspond with them to thank them for all the hard work that they put in on behalf of the journal. It would not be successful without them.As an electronic journal we have the option of doing things not possible with a print journal; one of these being the use of short video sequences or loops as part of a manuscript. The JACMP is interested in initiating this option and we will be working on it during the year.Peter R. Almond, Ph.D.Editor‐in‐Chief


BioMed Research International has retracted the article titled “Anaerobic Treatment of Palm Oil Mill Effluent in Pilot-Scale Anaerobic EGSB Reactor” . The art


While the benefits of EVH include reducedwound complications and improved cosmetic outcome, an inferior patency rate of EVH-SVscompared to those harvested by open vein harvesting (OVH) has beenreported[3] ([4]. This decision was based on data from the Project ofEx-vivo Vein Graft Engineering via Transfection (PREVENT) IV trial, where EVH-SV graftsshowed higher failure rates than OVH grafts and, at 3 years, a higher death rate,myocardial infarction or revascularization compared to OVH grafts[5]. Originally, the PREVENT IVtrial was designed as a randomized controlled trial to assess the effectiveness andsafety of edifoligide on angiographic SV graft failure 12-18 months following CABG, aswell as the effect of edifoligide on major adverse cardiac events throughout 5 yearsafter CABG. Considering that the study by Lopes et al.[5] is a secondary analysis, theresults should be evaluated carefully and potential biases inherent to a non-randomizedstudy design should be considered. However, data published subsequently included morepatients and, although it was judged that "EVH did not show increased occlusion rates orincidences of reintervention, myocardial infarction or death for endoscopicallyharvested grafts...the Committee noted the importance of training and regular experiencefor any clinician doing this procedure" [4]. Simultaneously, the 2014 Guideline on MyocardialRevascularization of the European Society of Cardiology (ESC) and the EuropeanAssociation for Cardio-Thoracic Surgery (EACTS) acknowledged the lack of unequivocalevidence concerning patency rates of EVH-SVs and no inferiority in clinical outcomesassociated with EVH[6].The saphenous vein (SV) is the most commonly used conduit for coronary artery bypasssurgery (CABG)orted[3] .Previou[7] showed endothelial damage in EVH-SV grafts anddemonstrated that cellular metabolic activity, viability and membrane damage to theendothelium is less in OVH compared with EVH grafts. Also, using optical coherencetomography, Kiani & Poston[8] described marked damage to the adventitia of EVH-SVgrafts as well as regions of endothelial denudation and abnormalities within the intimaand deeper vessel layers, damage likely to affect graft patency.The unfavorable results regarding EVH-SV grafts are due to vascular damage inflictedwhere they are subjected to vascular trauma, including traction, adventitial stripping,and venous compression. Rousou et al.. This data is supported by a recentrandomized trial from the Swedish group, which compared no-touch SV patency to theradial artery, providing further evidence for the superiority of no-touch SVgrafts[11].This is important given the general consensus amongst cardiac surgeons that radialartery patency is superior and therefore the second conduit of choice. While theincidence of wound complications in patients receiving no-touch SV is higher than inthose receiving EVH grafts, they are similar to patients receiving OVH grafts and theirperformance is far superior, at ~90% vs. 50% long-term. Several studieshave reported SV graft failure rates of up to 10% to 20% after 1 year and an additional5% failure rate for each subsequent year with conventional OVH. When performing OVH, the recent 2014 ESC/EACTSGuidelines on myocardial revascularization support the use of the notouch technique toreduce graft injury and improve patency[6]. There is evidence that the improved patency ofno-touch SV over conventional OVH grafts is associated with a reduction in vasculardamage[15],maintaining normal vessel architecture, preservation of an intactendothelium and endotheliumderived NO[17], as well as preservationof the vasa vasorum and the SVs surrounding cushion of perivascularfat. The damage inflicted to the SV using both OVH and EVHaffects both short- and long-term graft performance. For example, reduced luminal nitricoxide availability, due to endothelial injury, leads to increased platelet aggregation,thrombus formation and early graft occlusion[12]. The results of the immunohistochemicalanalysis with CD34, iNOS and three isoforms of nitric oxide synthase in the human SVremoved conventionally showed an evident impairment of the endothelialfunction[22-24]. Damage to the outer layers of the SV, in particularthe adventitial vasa vasorum, reduces transmural blood flow, resultingin medial ischemia, conditions that have been shown to promote neointimal hyperplasiaand atherosclerosis, thereby affecting mid- and long-term graftpatency[19]. The cushion of perivascular fat that remains intactusing no-touch technique is an important source of adipocyte-derived vasodilatorfactors, suggested to play an important role in preventing venospasm at harvesting andpost implantation[20]. In addition, this pronounced outermost layer of fatprevents kinking of excessively long grafts and provides mechanical support thatprotects the vein once it is subjected to arterial hemodynamics at completion of distalanastomoses and removal of arterial clamps[18-21].At the time that EVH was described, an atraumatic, no-touch technique of harvesting theSV was introduced that, for up to 16 years, provides a superior graft with a patencyrate comparable to the internal thoracic artery (ITA)[3].EVH was recommended  to reduce wound-related complications, improvepatient satisfaction, and decrease postoperative pain, hospital length of stay, andoutpatient wound-management resources when compared with OVH[25]. While wound complicationsare reduced using EVH compared with OVH and no-touch-harvested SVs, graft performance ofEVH grafts may be inferior[25]. Early no-touch SV harvest site complications have beenreported to range from 11% to 18%[25], considerably higher when compared to EVH, althoughsimilar to conventional OVH[25]. Furthermore, the learning curve for EVH islonger[3],and although it has been suggested that EVH is a cost effective method for harvestingthe SV, the 2005 Consensus Statement of the International Society of Minimally InvasiveCardiothoracic Surgery (ISMICS) concluded there was inadequate cost-effectiveness datato allow recommendations on the resource implications of OVH vs. EVHtechniques[25]. Several recommendation statements and guidelines haveemphasized the importance of experience when performing EVH. Interestingly, although EVH may reducewound complications, the recent study by Te Kolste et al.[26] describes aspects of acutecompartment syndrome, a rare, but serious, limb-threatening condition that may occurafter CABG, especially following EVH. It is noteworthy that, over 10 years ago in theirexcellent review, Shuhaiber et al.[27] stated "In the operating room, tissue manipulationand the role of the surgeon or surgical assistant is quite essential. The no-touchtechnique of handling tissues during harvesting should be adopted in order to preservethe endothelial integrity and function."Considering the dramatic improvement reported for notouch SV grafts, it is surprisingthat this technique is limited to a few cardiac centers, mainly in Sweden and Braziland, at a rough estimate, amount to less than 1000 cases per year worldwide. The reasonsfor this low take up rate are unclear, but may be associated with senior surgeons'resistance to change and/or unwillingness to "retrain", rather surprising given therapid adoption of EVH to a present level of over 80% of all CABG in theUSAEVH is becoming popular in patients undergoing CABG in Brazil, a situation most likelyinfluenced by the low wound healing complications and improved cosmetic outcomeassociated with this technique, in addition to its favored use in the USA. Whenconsidering the extra cost and problems regarding EVH-SV graft performance as describedabove, should the patient be made aware of the potential benefits of no-touch SV grafts?Should the benefits of no-touch SV harvesting be discussed and should the patient begiven a choice?


Physiological analysis indicated that ETH accelerated starch degradation and increased soluble solids content (SSC) and soluble sugars , while CA inhibited starch reduction compared with NA. Using these materials, expression patterns of 24 genes that may contribute to starch degradation (seven previously reported and 17 newly isolated) were analyzed. Among the 24 genes, AdAMY1, AdAGL3 and AdBAM3.1/3L/9 were significantly induced by ETH and positively correlated with starch degradation. Furthermore, these five genes were also inhibited by CA, conforming the likely involvement of these genes in starch degradation. Thus, the present study has identified the genes with potential for involvement in starch degradation in postharvest kiwifruit, which will be useful for understanding the regulation of kiwifruit starch content and metabolism.Starch is one of the most important storage carbohydrates in plants. Kiwifruit typically accumulate large amounts of starch during development. The fruit retain starch until commercial maturity, and its postharvest degradation is essential for consumer acceptance. The activity of genes related to starch degradation has, however, rarely been investigated. Based on the kiwifruit genome sequence and previously reported starch degradation-related genes, 17 novel genes were isolated and the relationship between their expression and starch degradation was examined using two sets of materials: ethylene-treated  vs. control  and controlled atmosphere stored (CA, 5% CO Arabidopsis mutants that synthesize less starch during the daytime and have lower starch degradation capacity at nighttime exhibited reduced growth rates [Starch is widely distributed in plants and accumulates in various organs, such as leaves, seeds and also tubers . Starch th rates ,5. In frth rates  and applth rates . During th rates , mangoesth rates , and banth rates , store ath rates . High stth rates . Thus, eSolanum tuberosum L.) plants [Arabidopsis, where analysis of transgenic or mutants has shown that GWD1, DPE1 and DPE2 are involved in starch degradation in leaves [AMY1, AMY2, AMY3 and PHS1 had limited effects [GWD reduction could inhibit starch synthesis under light [GWD was also involved in starch granule morphology formation [Multiple enzymes have been reported to be involved in starch degradation, such as glucan, water dikinase  2.7.9.4), α-amylase , β-amylase , α-glucosidase , pullulanase , isoamylase , α-glucan phosphorylase  and 4-α-glucanotransferase . However, the key regulators of starch degradation vary between different plants, organs and even developmental stages. For instance, GWD was involved in starch degradation in tubers and leaves of potato  plants ,14, whil) plants . Anothern leaves ,17,18, w effects ,20. Howeer light , and GWDormation .Arabidopsis) and staple crops , starch research in fruit, mainly bananas and kiwifruit, has usually only been conducted at the physiological and biochemical level. During the ripening of bananas, activities of AMY, BAM and AGL increased and showed close correlation with starch degradation [MAmy, Ma-bmy, Maisa [phoI and phoII [Ma-bmy showed increasing expression patterns during postharvest storage [AdAMY1-3, AdBAM1, AdBAM3.1, AdBAM3.2 and AdBAM9) were reported using a kiwifruit expressed sequence tags (EST) database [Unlike model plants  are likely to differ, as starch is degraded to maltose, glucose and glucose 1-phosphate in Arabidopsis leaves, but could not be converted to maltose in kiwifruit [Moreover, the mechanisms of starch degradation in fruit (at least kiwifruit) and model plants  were applied to manipulate kiwifruit postharvest ripening and softening. Using the kiwifruit genome database, genes that encoded AdAMY (AdAMY1-3) and four AdBAM  genes were reported and analyzed for starch metabolism during kiwifruit development [Arabidopsis homologs and the known kiwifruit genes, these seventeen newly isolated genes were designed as three AdAGL , four AdBAM , three AdISA , two AdDPE , AdGWD  and AdPHS , and one AdPU  (Three elopment . In addiX383652) .A. deliciosa “Hayward”) soften after harvest during storage at 20 °C and ethylene treatment (ETH) rapidly accelerates the fruit softening progress [Kiwifruit , while differences in transcript abundance of AdBAM3.1 and AdAGL3 mainly occurred at a later stage (56 days and afterwards)  .Maintenance of texture is important for postharvest fruit storability and transportability. Most fruit undergo softening when detached from the tree, resulting from cell wall degradation and reduction in intracellular adhesion . In someDespite the importance of starch degradation to both softening and flavor of postharvest kiwifruit, starch-related enzymes and genes have only been studied during kiwifruit development and rarely during postharvest softening. Here, 24 genes potentially related to starch degradation were isolated based on the kiwifruit genome, including 17 novel genes and seven previously studied in developing kiwifruit  were invAdAMY1, AdAGL3 and AdBAM3.1/3L/9, were identified as having the greatest potential for involvement in starch degradation in postharvest kiwifruit. As shown in Ma-bmy was reported to be associated with banana fruit starch degradation according to transcript accumulation [GWD and DPE are necessary in potato and Arabidopsis, but their transcript levels were quite low during the major starch degradation process of kiwifruit. On the other hand, AMY showed the potential to regulate both banana and kiwifruit starch degradation, which may suggest some overlap mechanisms between different fruit.Taking the results from ethylene treatment (accelerate fruit softening and starch degradation) and CA storage (inhibit fruit softening and starch degradation) together, five genes, including mulation , and theActinidia deliciosa (A. Chev.) C.F. Liang and A.R. Ferguson var. deliciosa “Hayward”) were chosen as experimental material and were collected and described in our previous report [−1 C2H4, 24 h, 20 °C) vs. control  and controlled atmosphere  vs. NA (0 °C).Mature kiwifruit . SSC measurements were conducted with 12 fruit replicates, with 4 fruit from each biological replicate. After SSC analysis, as well as firmness analysis , the outd-glucose control were read at 510 nm against the reagent blank with UV2550 . Glucose, fructose and sucrose extractions and measurements were conducted according to the protocol of Lisec et al. [g for 10 min, the supernatants were transferred to new tubes and were mixed with 750 µL chloroform and 1400 µL dH2O. Then, the mixtures were centrifuged at 2200× g for 15 min. Aliquots of 100 µL of the supernatants were dried in vacuum  and 20 µL ribitol (0.2 mg·mL−1) was included in each sample as an internal standard. The residue was dissolved in 40 µL of 20 mg/mL pyridine methoxyamine hydrochloride, and incubated for 1.5 h at 37 °C. The sample was then treated with 60 µL Bis (trimethylsilyl) trifluoroacetamide (1% trimethylchlorosilane) for 30 min at 37 °C. The soluble sugars were measured by GC , A volume of 1 µL for each sample was absorbed with a split ratio 10:1 and injected into the gas chromatograph fitted with a fused-silica capillary column . The injector temperature was 250 °C and the helium carrier gas had a flow rate of 1.0 mL/min. The column temperature was held at 100 °C for 1 min, increased to 184 °C with a temperature gradient of 3 °C/min, increased to 190 °C at 0.5 °C/min, held for 1 min, increased to 280 °C at 15 °C/min and then held for 3 min. The significant MS operating parameters were as follows: ionization voltage was 70 eV, ion source temperature was 230 °C and the interface temperature was 280 °C.Starch and soluble sugar  measurements were conducted with frozen materials described above in three biological replicates. Total starch was extracted from 0.1 g frozen samples for each replicate following the procedures of the total starch assay kit , as described by Stevenson et al. . The absc et al. . SolubleTotal RNA extractions were conducted according to the method described by Yin et al. . The genAdAMY1-3) and β-amylase genes  [Starch degradation-related genes mentioned in research on starch metabolism during kiwifruit development, such as α-amylase genes ( AdBAM9) , were se AdBAM9) , additiohttp://tree.bio.ed.ac.uk/software/figtree/). Accession numbers for Arabidopsis genes in The Arabidopsis Information Resource (TAIR) are as follows: AtAMY1-3 ; AtBAM1-9 ; AtISA1-3 ; AtPU1 (Genbank no. At5g04360); AtPHS1-2 ; AtGWD1-3 ; AtDPE1-2 ; and AtAGL1-5 .Alignment was performed using the neighbor-joining (NJ) method in ClustalX  and phylogenetic analysis was performed with online software Figtree  and are listed in AdACT was chosen as the internal control [For real-time PCR, all primers were designed with online software primer3  was calculated with DPS . Figures were prepared with Origin 8.0 .AdAMY1, AdAGL3 and AdBAM3.1/3L/9, were characterized, using various postharvest treatments, as having higher potential to be involved in starch degradation during kiwifruit postharvest ripening. This has provided more specific targets for determining the mechanism and regulation of starch metabolism in kiwifruit. The potential complexity, however, with the involvement of multiple genes, may increase the difficulty for modification by transgenic or classical breeding approaches. Thus, it will be important to find the master regulators  for these five genes in future studies.In conclusion, seventeen genes encoding enzymes related with starch degradation were newly identified and isolated based on the kiwifruit genome, expanded in this catalog in kiwifruit from seven  to 24 ge


Zoological Research (ZR). In recognition of its impressive progress and great potential to develop into a leading journal in the field, ZR is now supported by the "Project for Enhancing International Impact of China STM Journals" (PIIJ) (Class B) (2016-2018). Having wide coverage, PIIJ is the most influential project in China for supporting and promoting the development of English language academic journal publications. In addition, ZR has achieved the "International Impact Academic Journal of China" title five years in a row. The year 2016 was a wonderful and important one for ZR depends on its unique niche in the field and the joint effort of its strong editorial team. Emphasizing the scope of ZR, namely, "Primates and Animal Models", "Conservation & Utilization of Animal Resources", and "Animal Diversity and Evolution", two special issues were released in 2016: "The Amphibian and Reptile Biodiversity of Qinghai-Tibetan Plateau" and "CRISPR/Cas9, Model Animals and Human Diseases". Moreover, to promote communication and collaboration among peer researchers, ZR is hosting the "2017 Frontiers in Zoology Symposium" in February 2017. The success of ZR continues to recruit local and overseas scientists to serve on its board. In 2016, ZR engaged four renowned scientists with varied expertise to join the vibrant ZR editorial team. These new board members include: Dr. Wai-Yee Chan, Chair Professor and Director, School of Biomedical Sciences, Chinese Hong Kong University, Hong Kong SAR, China; Dr. LeAnn Blomberg, Beltsville Agricultural Research Center (BARC), United States Department of Agriculture, USA; Dr. Hua-Xin (Larry) Liao, Professor, College of Life Science and Technology, Jinan University, China, and Professor, Duke University, USA; and Dr. Meng-Ji Lu, Professor, Institute of Virology, University of Duisburg-Essen, Germany. In addition, Dr. Guojie Zhang, a well-known expert on animal genomics who holds a position at the China National GeneBank, BGI-Shenzhen, and the Department of Biology, University of Copenhagen, as well as a guest professorship at the Kunming Institute of Zoology, Chinese Academy of Sciences, will also join the editorial board. With these new members, the editorial board of ZR now includes 48 distinguished scientists with expertise across multiple disciplines. To further strengthen the editorial board and widen its scope of expertise, ZR has continued to promote and market the journal during this past year. A new and more interactive homepage was launched and, as an open access journal, full-text articles can be downloaded via the homepage, PubMed Central, and SciEngine. To expand our readership, abstracts of published articles are also available online in Chinese. Information regarding the new initiatives and measures of ZR will continue to be shared with our readers through our official WeChat account (ZoolRes). In addition, ZR has now been indexed by Scopus and other related databases, and has a CitesScore value of 0. 48 and ranks 786 among 1 549 journals in the subject "Medicine". To further its scientific reach, ZR will continue to publish innovative zoological studies and advance knowledge in scientific research. With the proud tradition of attracting outstanding scholars with diverse backgrounds and expertise to write for the journal, as well as the hard work and dedication of our editors and editorial board members, ZR has become a representative international scientific journal in animal studies. With a growing number of international submissions and article citations, as well as an increasing impact factor, we believe that ZR will confidently march into its thirty-seventh year and accomplish its goal of becoming an iconic journal in animal research. ZR could not have achieved what it has without the support of you, our readers. It is a journal that belongs to all members of the animal research community, and we look forward to continuing to work with you all to nurture and carry ZR to the next stage in 2017. SincerelySchool of Biomedical Sciences, The Chinese University of Hong Kong, ChinaWai-Yee Chan, Executive Editor-in-Chief Kunming Institute of Zoology, ChineseAcademy of Sciences, Kunming 650223, ChinaYong-Gang Yao, Editor-in-Chief


Ischemic injury during organ transplantation increases the risk of acute and chronic rejections by promoting alloimmune responses. Measurement of neutrophil gelatinase-associated lipocalin (NGAL) immediately after kidney transplantation may be promising for early detection of ischemic injuries to allograft.This study assessed possible predictive values of plasma NGAL levels during first hours after kidney transplantation for graft loss within the first 3 months after transplantation.45 kidney transplant recipients were classified into those without graft loss or with graft loss during 3 months after transplantation. Plasma NGAL levels were measured before and at 2, 6, 12, 24 and 96 hours after transplantation. Serum creatinine concentration was assessed daily during hospitalization and at 1, 2, and 3 months post-transplantation.Serum creatinine and plasma NGAL levels were consistently higher in patients with graft loss compared with those without graft loss. At 2, 24, and 96 hours after transplantation, plasma NGAL concentration was significantly higher in patients who developed allograft loss within 3 months post-transplantation. The cutoff point of plasma NGAL at 2, 24, and 96 hours after transplantation for prediction of graft loss was 304.5 ng/mL , 207.8 ng/mL, and 184 ng/mL , respectively.Plasma NGAL levels at 2, 24, and 96 hours after transplantation can predict 3-month graft loss with fair sensitivity and specificity. Kidney transplantation is the treatment of choice in patients with end-stage renal disease. Kidney transplant recipients have better quality of life than patients undergoing dialysis . Severalde novo NGAL synthesis [Therefore, we need to use non-invasive and sensitive markers to diagnose subclinical ischemic graft injury early and treat patients timely and individually to prevent future acute rejections and graft loss. Measurement of urine or blood biomarkers such as neutrophil gelatinase-associated lipocalin (NGAL), cystatin C, interleukin 18 (IL-18), and kidney injury molecule 1 (KIM)-1 immediately after transplantation for early prediction of acute kidney injury (AKI) have been proposed as the most promising biomarkers . NGAL isynthesis . Althougynthesis -14 or blynthesis -20 NGAL ynthesis -24 or seynthesis  NGAL on In this study, we aimed at measuring serial plasma NGAL during the first hours after transplantation in recipients of deceased donor kidney and examining whether kidney injuries detected only by increased level of plasma NGAL can affect graft outcome within the first three months after transplantation regardless of early graft function. We also assessed predictive value of plasma NGAL during early hours after transplantation on graft function and survival within three months after transplantation.Study Design and PatientsPneumocystis jeroveci pneumonia and candidiasis, respectively. The cold and warm ischemia times were kept shorter than one hour in order to minimize the impact of ischemia on the allograft. This cross-sectional study was conducted at kidney transplantation ward of Imam-Khomeini Hospital complex affiliated to Tehran University of Medical Sciences, Tehran, Iran. Forty-five patients aged more than 14 years who underwent kidney transplantation from deceased donor for the first time were included. All enrolled patients received the same immunosuppressive regimen according to our protocol. All patients received thymoglobulin induction and prednisolone, mycophenolate mofetil and tacrolimus as maintenance immunosuppressive regimen. Prednisolone dose was tapered down to 5 mg/day within one month after transplantation in all patients. The desired whole blood trough tacrolimus concentration was 8–12 ng/mL. All patients received intravenous ganciclovir/oral valganciclovir, oral cotrimoxazole and clotrimazole for prophylaxis of cytomegalovirus, Data Collection, Graft Function and Survival AssessmentAll demographic data  and considerable information before transplantation  from the donor and recipient were gathered. Daily measurement of urine output and serum creatinine were started on the day of transplantation and continued until discharge of patient from the hospital. All patients were monitored within three months of transplantation; all aspects of graft function, serum creatinine, infections, and other complications were recorded. Creatinine reduction rate (%) was calculated as the difference between serum creatinine at the target day and the day before, divided by serum creatinine at the target day, multiplied by 100. Graft function three months after transplantation was evaluated by measuring serum creatinine level. In patients with graft loss, the last serum creatinine measured prior to dialysis restart, was considered for 3-month serum creatinine.Graft survival was evaluated based on the number of patients’ grafts that were not lost within three months after kidney transplantation. Graft loss was considered if a patient needed maintenance dialysis within three months of transplantation. Graft losses due to vascular and urological surgery complications, ureteric obstruction, renal artery stenosis, and infections were not included. Number of possible or proven cellular/humoral rejection episodes within 3-month follow-up was also evaluated.Sample Collection and Plasma NGAL AssayA baseline blood sample was taken upon patient arrival to the transplant unit before transplantation. Post-transplantation samples were collected at 2, 6, 12, 24, and 96 hours following the transplantation. Samples were immediately processed and stored at 70 °C. We utilized a commercial double antibody sandwich enzyme-linked immunosorbent assay (ELISA) kit  for measuring plasma NGAL concentrations. Serum creatinine level was determined preoperatively, daily until hospital discharge, and at 1, 2, and 3 months after transplantation using Jaff´e method.Statistical Analysis® for Windows® ver19.0 . Normality of variables was tested by the one-sample Kolmogorov-Smirnov test. Data are expressed as mean±SD for normally distributed variables and as median and IQR for variables not normally distributed. Baseline characteristics and biochemical data of the patients with and without graft loss were compared by two-sample Student’s t test. χ2 and Fisher’s exact tests were used in analyses of contingency tables. Student’s t test was used for samples with normal distribution; the Mann-Whitney U test was used for analysis of data not normally distributed. Bivariate correlations were analyzed using the Spearman’s ρ or λ correlation coefficient for non-parametric, and the Pearson’s correlation coefficient (r) for parametric measures of statistical dependence. A receiver operating characteristic (ROC) analysis was generated at 2, 6, 12, 24, and 48 hours after kidney transplantation to determine the cut-off value for plasma NGAL and serum creatinine and their potential to predict graft loss within 3-month follow-up. A p value of <0.05 was considered statistically significant.Data were analyzed using SPSSEthicsThe study protocol was approved by the local Ethics Committee of Tehran University of Medical Sciences. Written informed consent was obtained from the recipients before enrolment.A total of 45 patients was assessed in this study. Demographic characteristics of the patients are shown in Although plasma NGAL levels were higher in kidney transplant recipients with expanded criteria donor compared with those with standard criteria donors, the difference was not statistically significant. No significant correlation was also found between plasma NGAL levels at all times and recipients’ age or pretransplantation dialysis time (data not presented).In addition, except for plasma NGAL level at 96 hours post-transplantation , plasma NGAL levels did not have any significant correlation with creatinine reduction ratios on post-transplantation day 2. It means that kidney transplant recipients with lower plasma NGAL measured 96 hours after transplantation had higher reductions rates in serum creatinine within two days of the transplantation. The median length of hospital stay after transplantation was 14 (IQR: 9.5–21) days. Plasma NGAL levels measured 2, 12, and 96 hours post-transplantation were strongly correlated with the length of hospital stay .Seven (16%) recipients experienced graft loss within three months of kidney transplantation. No significant difference was found between “graft loss” and “no graft loss” patients in terms of baseline demographic and clinical characteristics and cumulative thymoglobulin induction dose . As expected, patients with graft loss within three months of transplantation had higher serum creatinine levels and lower creatinine reduction ratios during the first week post-transplantation, although these changes were not significant compared with “no graft loss” patients .Similar to serum creatinine, the median plasma NGAL concentrations in the first hours post-transplantation were consistently higher in patients with “graft loss” compared with “no graft loss” at most measured time points . Compared with patients without graft loss, the changes in plasma NGAL over time in patients with graft loss were characterized by first increased in plasma NGAL concentrations from baseline values followed by a decrease in plasma NGAL levels and remaining high thereafter. ROC analysis showed that plasma NGAL levels in all time points could fairly an accurate predictor for graft loss within three months after transplantation . Areas u2) 1, 2, and 3 months after transplantation.To evaluate the prognostic value of plasma NGAL levels for three-month graft function, we explored the correlation between plasma NGAL levels before transplantation and at the first hours post-transplantation with serum creatinine and estimated glomerular filtration rate (eGFR) assessed 1, 2, and 3 months post-transplantation. Although plasma NGAL levels showed positive correlation with serum creatinine concentrations and negative correlation with eGFR at the day of hospital discharge and also at 1, 2, and 3 months after transplantation in all patients, the correlations were not statistically significant (data not shown). ROC analyses were performed to assess plasma NGAL’s ability to predict poor graft outcome in the first, second, and third month after transplantation. Plasma NGAL levels in all time points were not significantly accurate for predicting low graft function  and 2 hours , 6 hours , 12 hours , 24 hours , and 96 hours  after transplantation with total number of rejection episodes during the first three months post-transplantation.The episodes of polyomavirus, cytomegalovirus, and bacterial infections did not differ between patients with and without graft loss within three months after transplantation . The epiThis prospective study showed that plasma NGAL level is a promising biomarker for predicting allograft loss within three months after kidney transplantation. We assessed plasma NGAL levels during the first hours of day 1 to day 4 after transplantation in a cohort of 45 kidney transplant recipients. At 2, 24, and 96 hours after transplantation, plasma NGAL concentrations were significantly higher in patients who developed allograft loss within three months post-transplantation. Plasma NGAL level shortly after transplantation was higher in patients who were going to develop graft loss within three months of transplantation. In addition, changes in plasma NGAL concentrations over time showed different kinetic patterns between patients with and without 3-month graft loss . RecipieWe think early post-transplantation plasma NGAL level might represent graft injury and thus, might predict graft loss during following days to months. Using ROC analysis, findings suggested plasma NGAL concentrations in early days after transplantation as a good diagnostic test to identify patients with graft loss within three months of transplantation. The AUC-ROC for plasma NGAL was fair accurate (AUC: 0.7–0.8) for graft loss prediction within three months after transplantation. Determination of the paired sensitivity and specificity for the cutoff value of plasma NGAL was performed based on the closest to the left upper corner of the unit square to predict the graft loss. Two hours after surgery, a cutoff plasma NAL level of 304.46 ng/mL had a sensitivity of 71.4% and specificity of 73.7% for identification of graft loss. At 24 hours after surgery, a plasma NGAL cutoff value of 207.8 ng/mL had a sensitivity of 85.7% and specificity of 60.5% for identification of the graft loss. On the fourth day post-transplantation, a plasma NGAL level higher than 184 ng/mL predicted graft loss with a sensitivity of 85.7% and specificity of 71.1%.2 and those with GFR >80 mL/min/1.73 m2 [So far, there has been no study to evaluate diagnostic and predictive values of plasma or urine NGAL for graft loss within early months after kidney transplantation using ROC analysis. In a study with longer follow-up period on pediatric kidney transplant recipients, no association was found between the amount of serum/urine NGAL at 1, 3, and 7 days post-transplantation and serum creatinine concentration at the first year after transplantation . The mea/1.73 m2 . We alsoet. al., found that higher urine NGAL level on day two post-transplantation was associated with a significantly lower 1-year allograft eGFR. In multivariate logistic regression analysis, urine NGAL concentration measured on day two post-transplantation was an independent predictor for long-term poor graft function (defined as eGFR <60 mL/min/1.73 m2) in 62 kidney transplant recipients [et. al. [Choi, cipients . They sucipients . Althougcipients , 22 evalcipients . In contcipients  did not cipients . Our res[et. al. . In theiet. al. [Hollmen, et. al. , suggestet. al., has proposed the hypothesis that urine NGAL is a more useful prognostic factor for post-operative subclinical tubular ischemic injury because significant extrarenal NGAL secretion in the recovery phase after surgery may mask any increased kidney secretion of NGAL into circulating blood [In contrast to other studies , 21-23, ng blood .According to the moderate association between the number of total rejection episodes within the first three months after transplantation and graft loss and evidence of strong association of number of humoral rejection within the first three months post-transplantation with graft loss, it seems that early identification and appropriate interventions for acute rejections ensure decrease in graft loss in long term.In conclusion, plasma NGAL levels at 2, 24, and 96 hours after kidney transplantation predicted 3-month graft loss with fair sensitivity and specificity. Nowadays, plasma/urine NGAL as an early biomarker for diagnosis of delayed graft function, is suggested in several studies -16, 19, Some advantages of our study included prospective design of the study and measurement of plasma NGAL levels at multiple early time points after kidney transplantation that provided the information about the pattern of change in plasma NGAL levels over time. However, we did not find any correlation between plasma NGAL concentration and graft function within three months post-transplantation. Nevertheless, it seems that following graft function for longer time after transplantation would be favorable. Our study has several limitations including the small sample size and being conducted as a single-center study. We suggest protocol biopsy for all patients to confirm even subclinical ischemic injuries and also use of other potential kidney injury biomarkers. Possibly, the results of this study and similar future studies help to early predict graft function in long term and consequently will assist clinicians to care about immunosuppressive regimen for patients with predicted worse graft function.


As the Editors-in-Chief of the official journal of the World Allergy Organization, we look back at the year 2016 with satisfaction , two uttermost current topics were addressed in 2016, rendering the following current recommendations: (1) Currently no evidence could be found for Vitamin D supplementation to be effective against allergies in children, neither in pregnant, nor in breastfeeding, women ; (2) PreOverall, the work published in 2016 in the WAO Journal reconfirmed that the constant global exchange and collaboration of allergy experts across international borders leads to novel recommendations and guidelines and contributes to an overall harmonization. We consider this important in the increasingly fast pace of change in medicine where evidence-based results have to be weighed out against market strategies for the best care of our patients.We are looking forward to receiving exciting contributions again in 2017!Erika Jensen-Jarolim, MD and Alessandro Fiocchi, MDVienna, Austria, and Vatican City, ItalyDecember 2016