In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system  quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range. Radio Frequency Identification (RFID) is one of the Auto Identification and Data Capture (AIDC) techniques, which enable objects to be automatically identified. With the advantages such as automation, no-contract, easy-to-implement and enough-durability, passive RFID is widely applied in various applications such as supply chain management , manufacAccording to most applications, a single reader cannot totally cover a specific area . Correspondingly, a classical RFID scenario is usually composed of multiple readers and large quantity of passive tags: the so-called Multiple-reader Environment (MRE). In classical MRE, multiple readers are deployed in different densities with known positions to interrogate the randomized tags with fixed positions under the same RFID system. To dynamically allocate the operating resources  and manage readers, centralized mechanism is usually designed to be executed by a coordinator device , which is connected to the readers through a wired or wireless network ,6. DurinControl-mechanism-based algorithms ,8,9 alloScheduling-based algorithms transform the multiple-reader interference problem into an optimization problem with respect to the allocation of operating resources e.g., ,11). Bas. Bas11])In the view of scheduling-based mechanism, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed as a resource allocation algorithm to fairly schedule the readers operating with low interferences and large effective interrogation ranges in centralized MRE. GD-MRSOA-AIS first produces several fair feasible scheduling schemes using geometric probability distribution to allocate the operating time slot and frequency channel, which could minimize the collisions among the readers contending for operating resources and therefore maximize the probability that one reader successfully gains the opportunity to operate. To optimize these feasible scheduling schemes with the objective of maximizing the total effective interrogation range, the artificial immune system optimization with immune clone, immune mutation and immune suppression is further introduced. During the mutation process in artificial immune system optimization, there are two alternative mutation operators for different cloned antibodies, where the single-bit mutation is suitable for the superior ones and the region-bits mutation is appropriate for the regular ones.By using signal-to-interference-plus-noise (SINR) to explain the reduction in interrogation range, a resource allocation model is constructed with two constraint conditions which are used to decrease the multiple-reader interference.A geometric probability function is introduced to replace the uniform probability function to produce the feasible scheduling schemes, which ensures that readers could operate in a fair way.Artificial immune system with clone operator, mutation operator and suppression operator is introduced to optimize the feasible scheduling schemes. In mutation process, both of the single-bit mutation operator and the region-bits mutation operator are imported to deal with the different cloned antibodies to accelerate the optimization process and convergence speed.Summarizing, the contributions of this paper are as follows:The remainder of this paper is organized as follows. In Readers are randomly distributed over an area in two dimensions.Any reader has only two states, active and inactive, where only the readers in active operate and interfere with other active ones.The interference power from multiple interfering readers seen by the desired reader is additive.In MRE, each reader transmits electromagnetic wave to create the interrogation range, where the size and shape of interrogation range depends on many factors ,18 such 1 is the desired reader, R1 could reach to the red circle as its maximum interrogation radius of max,r1 without any interference. When R1 attempts to detect the target tag A, if the signal is masked by the interfering reader R2 and R3 (the interfering range is represented by the black circle), the effective interrogation range r1 (blue circle) of R1 will decrease from max,r1. If r1 is smaller than the distance x between R1 and tag A, R1 could not detect this target tag A. Moreover, target tag B located in the overlapped range of r1 and r3 is hardly detected due to the multiple electromagnetic waves from R1 and R3 simultaneously operating.A simple centralized MRE is illustrated as max,ir of Ri is related to the hardware design ) to mark the readers located in the range of f-mind, where Ri is suffered from the first kind interference if the readers from RiIS are simultaneously operating at the same frequency channel with Ri  for any two Ri and Rj. Therefore, Ri with any Rj in its RiIS (j ≠ i) should be operating at different frequency channels as: iCH(k) j≠ CH(k) if j∈RiIS and j ≠ i, where iCH(k) denotes the frequency channel numbers selected by Ri at the kth time slot.Based on the relative distance jω(k) = 0 if j,id ≤ s-mind)f-mind, another smaller distance denoted as s-mind exists, where Ri is suffered from the second kind interference if readers located in s-mind are operating simultaneously even if they are at different frequency channels because they are overlapped in the effective interrogation range , which is listed in Further, in i with Rj in s-mind should be operating non-simultaneously as: jω(k) = 0 if j,id ≤ s-mind), where jω(k) denotes the 0–1 function of Equation (3).Therefore, RS) to schedule ReaderN readers operating with SlotN time slots and FreqN frequency channels. Note that NR = {1, 2, 3, …, ReaderN}, NS = {1, 2, 3, …, SlotN}, CH = {1, 2, 3, …, FreqN}, WS = {|ix∈, iy∈} and RiIS = {j|j∈NR, j,id < f-mind}.Constricted by the constraint conditions, the resource allocation model is finally constructed as Equation (8) with the objective of maximizing the total effective interrogation range (denoted as GD: Geometric distribution function (GD) combined with the fairness consideration is introduced to randomize the feasible scheduling schemes with lower interferences which satisfy the constraint conditions in Equation (8). Details are described in AIS: Artificial immune system optimization (AIS) is to optimize these feasible scheduling schemes as the optimal scheduling scheme for readers fairly operating with larger effective interrogation range. Details are presented in According to the proposed resource allocation model, GD-MRSOA-AIS is proposed to fairly allocate the operating resources with lower reader interference and larger effective interrogation range. In GD-MRSOA-AIS, it is composed of two parts:According to the constraint conditions in Equation (8), GD-MRSOA-AIS will first produce several feasible solutions as the feasible scheduling schemes to ensure that readers could fairly operate with low signal interference.1, R2 and R3 in 4 in In centralized MRE, both the interference-reader . Here, NeighborN(i) is the cardinality of RiIS for Ri, where NeighborN(i) = 1 denotes that there is no neighbors located around Ri and therefore Ri is an isolated reader without any possible interference.For NeighborN(i) = 1, then iα = 1, and i with bigger NeighborN(i) could easily wins the kth time slot as a higher p(k)i while Rj with smaller Neighbor(j)N has to select the operating time slot like uniform distribution as a lower p(k)j.Note that when Sift_Function, it generates several feasible scheduling schemes for readers operating with the allocated time slots and frequency channels, where the feasible scheduling schemes are restricted by the constraint conditions in Equation (8). Therefore, each feasible scheduling scheme produced by Sift_Function is actually a feasible solution for Equation (8), where the pseudocode is summarized as Algorithm 1.By using Algorithm 1: Pseudocode for Feasible Solutions Generation by Sift_FunctionSift_Functioni = 1;1 set i ≤ ReaderN do2 while 3  set 4  set ik=SlotN;5  set z = 1 to SlotN do6   for il then // Contend for operating time slot7    if i = z;ki is operating at zth time slot// R8      set 9      break;10     end if11    end forCHi(ik) from CH; i// Allocate a frequency channel for R12    randomize j = 1 to ReaderN and j ≠ i do13    for j∈RiIS then //CHi(k) ≠ CHj(k) if j ∈ISRiConstraint Condition: 14      if CHj(ik) from CH-{CHi(ik)};15     randomize j,id ≤ s-mind(|CHj(ik)-CHi(ki)|) then //j(k) = 0 if dj,i ≤ ds-min)ω16     if CHj(ik) = 0;17        set 18     end if19     end if20     end fori++;21     22  end whileFor each feasible solution of Equation (8), the total effective interrogation range might be not large enough. Therefore, this feasible scheduling scheme might be not the optimal one to maximize the global effective interrogation range. To optimize these feasible scheduling schemes, the artificial immune system optimization is introduced in the following section.Sift_Function and the antigen corresponds to the objective function of Equation (8) with the constraint conditions. According to this, the affinity function could be formulated as Equation (10), where the process for optimizing the feasible solutions of Equation (8) is transformed to find the maximum affinity value of Equation (10) and its corresponding optimum antibody.For the produced feasible scheduling schemes, they could be optimized by using artificial immune system optimization, where each candidate antibody corresponds to one feasible solution of Equation (8) produced by GenN generations, where it exists three phases in every iterative generation as: immune clone, immune mutation and immune suppression/recruitment. In the clone phase, each antibody is acted as a parent to be correspondingly cloned for a fixed number of CloneN children antibodies, and all children antibodies go through the mutation process but only one child antibody with the highest affinity-value among the children antibodies is selected to compare with its parent antibody. If this selected child antibody is superior to its parent antibody in affinity value, it will replace its parent antibody as a new generation. Once the affinity value of this new generation is not significantly different from that of the previous generation, the suppression will be triggered, where the SP antibodies with lowest affinity-values are suppressed. Then, the corresponding numbers of antibodies produced by Sift_Function are recruited. This process is repeated until GenN iteration is met. The related symbols and their descriptions are listed in The proposed artificial immune system optimization is predefined to iterate IniN antibodies (feasible solutions) are randomized by repeatedly run Sift_Function in IniN times to construct the candidate antibody population set as AB = {Ab(u)|u∈}.To initialize the optimizing process by using artificial immune system, Ab(u) in AB, it is encoded as integer type since both frequency channels and time slots are discrete distribution as integer type. Seen from Ab(u) consists of ReaderN segments as ab(u)1, ab(u)2, ab(u)3,…, ab(u)NReader, where each ab(u)i is actually corresponding to a reader Ri and it includes a sequence of bits as iCH(1), iCH(2), iCH(3),…, iCH(SlotN) where each iCH(k) is denoted as the selected frequency channel of reader Ri at the kth time slot. iCH(k) = 0 means that reader Ri does not operate at this kth slot.For each antibody AB = {Ab(u)|u∈}, each Ab(u) is regarded as an parent antibody. For each parent antibody Ab(u), CloneN cloned antibodies with the same encodings are produced as its children antibodies, in which these children antibodies will go through the mutation operation to increase the diversity and therefore they have more potential to evolve as excellent individuals. Here, CloneN is required to be predefined as the cloned multiplier, and each Ab(u) has a clone pool as AB(u)Clone = {Abc(c)|c∈} to store its children antibodies, where each Abc(c) in AB(u)Clone is encoded as After producing the candidate antibody population set as Abc(c) from the clone pool AB(u)Clone is totally the same as its parent antibody Ab(u) in every bit before the mutation operation.Note that each child antibody Abc(c) Clone = {Abc(c)|c∈} of its parent Ab(u), there are two optional mutation operators as: single-bit mutation operator is applied for the ones with higher affinity values and region-bits mutation operator is applied for the ones with lower affinity values.For each child antibody c) i.e., b from thiCH(k) is randomly selected as a hotspot to be mutated following the constraint conditions, which belongs to a reader Ri  is also a feasible scheduling scheme as well.For single-bit mutation operator, only one bit Ri i.e., b. As a riCH(k) increasing L-bit length, note that L is less than SlotN minus k to guarantee the mutation is happened in one reader Ri  is also a feasible scheduling scheme.For region-bits mutation operator, a contiguous region bits are selected to be mutated starting from a hotspot of Ri i.e., b. In addBy single-bit mutation, the children antibody could extremely inherit the superior bits of the parent antibody while the children antibody would have more potential to mutate as the superior ones by region-bits mutation. Both of them could fast the convergence and quickly reach to the global optimization.The single-bit and region-bit mutation operator run as in Algorithms 2 and 3 respectively.Ab(u) , its children antibodies Abc(c) from the clone pool AB(u)Clone = {Abc(c)|c∈} are totally different: some Abc(c) surpasses Ab(u) in affinity value while some of Abc(c) are identical or inferior to Ab(u). To distinguish them, all Abc(c)  should be sorted by affinity value. Select the Abc(c) with highest affinity value and compare it with its parent antibody Ab(u): if this Abc(c) is superior to its parent antibody Ab(u), it will replace its parent antibody as a new candidate antibody in AB.After the mutation operations, for each parent antibody Algorithm 2: Pseudocode for Single-bit Mutation Single-bit _Operator iCH(k) of Ri from Abc(c) to be mutated; 1 Randomly determine a bit j = 1 to ReaderN and j ≠ i 2 for RjIS∩RiIS ≠ ∅ 3   if CH = CH-{jCH(k)}; 4    5   end if 6 end forCH ≠ ∅ 7 if iCH(k) from CH; 8   Randomize  9 elseiCH(k) = 0; 10    11 end ifAlgorithm 3: Pseudocode for Region-bits Mutation Region-bits _Operator iCH(k) of Ri from Abc(c) to be mutated; 1 Randomly determine a bit q = k; q ≤ k + L; q++) 2 for(j = 1 to ReaderN and j ≠ i 3 for RjIS∩RiIS ≠ ∅ 4 if CH = CH-{jCH(q)}; 5  6 end if 7 end forCH ≠ ∅ 8 if CHi(q) from CH; 9 Randomize  10 elseCHi(q) = 0; 11  12 end if 13 end forAB is significantly increased, this AB will be directly regarded as a new generation and go through the same immune process via clone operation, mutation operation and suppression operation.After the mutation operation, the candidate antibodies are changed. If the affinity value of new candidate antibody population set SP percentage of antibodies with lowest affinity values. After that, SP of IniN antibodies (feasible solutions) are produced by Sift_Function, where these fresh candidate antibodies are recruited in AB to compose a new generation population. In addition, this new generation population will go through the same immune process via clone operation, mutation operation and suppression operation.On the contrary, the candidate antibodies with highest affinity values should be promoted while the antibodies with lowest affinity values should be suppressed. Sorted by the affinity value, it will suppress genN, GD-MRSOA-AIS terminates. Finally, the pseudocode for proposed artificial immune system (proposed-AIS) optimization in GD-MRSOA-AIS is listed as Algorithm 4, where the corresponding flowchart is shown in When the iteration reaches the predefined maximum generations Algorithm 4: Pseudocode for Optimal Scheme Generation by using proposed-AIS OptimizationAIS_OptimizationIniN, Clone, NGenN, SP;1  Set 2  int t, u, c;3  float aff_old, aff_new;4  Initialization: Run Sift_Function in IniN times to construct set AB;5       Evaluate the affinity value of all elements in AB and average them as aff_old;t< GenN do6  while u = 1; u ≤ IniN; u++)7   for9    for 17     Sort the candidate antibodies by their affinity values;SP antibodies with lowest affinity values;18     Suppress SP new recruited antibodies by Sift_Function satisfying the constraint conditions;19     Produce 20   end if21 end whileSift_Function (denoted as GD-MRSOA-AIS) and without Sift_Function (denoted as MRSOA-AIS) will be simulated and compared with the state-of-the-art algorithm  in two 2 . As readers communicate with tags by means of EPCGlobal C1G2, the parameter settings are same with the ones listed in During the simulations, readers are randomly distributed over an area in two dimensions with 100 × 100 mSlotN is finally assigned as 5 in the following simulations. In addition, as the number of available frequency channels increases, the total effective interrogation range always increases since each reader has more options for selecting an available frequency channel to simultaneously operate with other readers at different frequency channels. Usually, the number of available frequency channels is set to no more than 10. Consequently, FreqN is assigned as 10 in the simulation. The parameters setting of proposed-AIS optimization in simulation are listed in Given a certain number of readers, as the number of available time slots increases, the readers have more options to avoid simultaneously operation. In other words, for a specific number of time slots, as the number of readers increases, the total effective interrogation range will be smaller, which is caused by the heavy interferences. Without the loss of generality, ReaderN = 15, the fixed positions of readers are randomized in ISR1 = {1, 3}, ISR2 = {2, 5, 6}, ISR3 = {1, 3}, ISR4 = {4, 7}, ISR5 = {5, 6, 8, 9}, ISR6 = {2, 5, 6, 8}, ISR7 = {4, 7}, ISR8 = {5, 6, 8, 9, 10, 11}, ISR9 = {5, 8, 9, 10, 11}, ISR10 = {8, 9, 10, 11}, ISR11 = {8, 9, 10, 11}, ISR12 = {12, 13}, ISR13 = {12, 13}, ISR14 = {14}, and ISR15 = {15}. Here, R14 and R15 are isolated readers since ISR14∩ISjR = ∅ (any j∈NR and j ≠ 14) and ISR15∩ISlR = ∅ (any l∈NR and l ≠ 15). On the contrary, i.e., ISR5∩ISR8∩ISR9∩ISR10∩ISR11 = {5, 8, 9, 10, 11}, these readers should be scheduled to operate at different time slots or simultaneously operate but at different frequency channels.When CHi(k) = 0 means that the ith reader does not operate at this kth time slot. At the first time slot (TS1) as green circles in 7, R9, R14, R15} are operating at the frequency channel of {CH7(1) = 5, CH9(1) = 7, CH14(1) = 1, CH15(1) = 10} using GD-MRSOA-AIS as in 11, R13, R14, R15} are operating at the frequency channel of {CH11(1) = 9, CH13(1) = 7, CH14(1) = 1, CH15(1) = 5} using MRSOA-AIS; and {R1, R4, R13, R15} are operating at the frequency channel of {CH1(1) = 7, CH4(1) = 1, CH13(1) = 10, CH15(1) = 3} using LIs algorithm. Take {R4, R7} as an example, ISR4∩ISR7 = {4, 7}. According to 4 is scheduled to operate at TS3 with the frequency channel of CH4(3) = 10 and R7 is scheduled to operate at TS1 with the frequency channel of CH7(1) = 5 by GD-MRSOA-AIS while R4 is scheduled to operate at every time slot as {CH4(1) = 1, CH4(2) = 3, CH4(3) = 1, CH4(4) = 1, CH4(5) = 3} and R7 is scheduled to be inactive at every time slot by LIs. Therefore in LIs, R4 is actually operating in uselessness especially for the last few time slots and it is unfair for R7. On the contrary, GD-MRSOA-AIS schedules R4 and R7 corporately operating in a fair way. The same scenario is also happened in {R12, R13}.Sift_Function, GD-MRSOA-AIS is obviously fairer since almost all readers (except for R1) are scheduled to operate at different time slots and frequency channels while both of MRSOA-AIS and LIs could not. For example, {R4, R5, R6, R7, R8, R10, R12} are always inactive in MRSOA-AIS and {R6, R7, R11, R12} are inactive in LIs  is the cardinality of RiIS. The JainI ranges from 0 to 1: the higher JainI means that the corresponding optimal scheduling scheme is fairer. Obviously, Ri with larger NeighborN(i) will make more contribution to obtain a bigger JainI. Therefore, the Jain Index could express the fairness of an optimal scheduling scheme.To evaluate the fairness of readers during the operating scheduling, a general purpose quantitative measure of fairness called Jain Index  is imporJainI = 18.22%, while the JainI of MRSOA-AIS is 8.89% and the JainI of LIs is 14.67% in the same scenario.As a result, GD-MRSOA-AIS becomes the fairest one with highest Jain Index of Sift_Function for time slots selection. Additionally, the average affinity value of both GD-MRSOA-AIS and MRSOA-AIS are much higher than LIs, where MRSOA-AIS rockets up to a high affinity value and then it stabilizes in the similar average affinity value like GD-MRSOA-AIS, which dues to the multiple mutation operations in the proposed-AIS. To achieve the average affinity value of 600, with GD-MRSOA-AIS and MRSOA-AIS, it costs around 50 generations while with LIs it is more than 150 generations. Therefore, the proposed-AIS also reduces the time consumption of optimization process.In ReaderN readers with SlotN = 5 and FreqN = 10 in the area of 100 × 100 m2, the position of each reader is randomly located. To ensure the convergence of the results, all the simulations are repeated for 50 times with 50 randomly positions. For an easier understanding, the results are listed in five indices  among GD-MRSOA-AIS, MRSOA-AIS and LIs algorithm, which are represented in For a given ReaderN = 4 with SlotN = 5 available time slots and FreqN = 10 frequency channels, readers are easily scheduled to operate at different time slots and frequency channels. Additionally, they could be deployed so sparsely that they are hardly interfered each other in such a large zone (100 × 100 m2). Therefore, the Jain Index is failed to measure the fairness. However, limited by the self-rated-power, the interrogation range is also finite. As a result, the total effective interrogation range is not large enough. As the number of readers increases, such as ReaderN = 24 and ReaderN = 28, positions of readers become much denser, the readers could not make full use of the frequency channels and the time slots, and then the individual effective interrogation range is declining and the total effective interrogation range relies on the cooperation among readers operating.When ReaderN = 8, ReaderN = 12, ReaderN = 16), each reader has fewer neighbors since they are sparsely distributed, which declines the Jain Index value even if all of the readers are scheduled to operate at least once. For the latter situations , readers are located in denser positions and so each reader has more neighbors, but some readers might be not scheduled to operate even once (iω = 0) which also decreases the Jain Index value. Even so, the Jain Index value of GD-MRSOA-AIS is also higher than MRSOA-AIS and LIs with the same number of readers.From ReaderN = 20, the mean effective interrogation range with GD-MRSOA-AIS is 3133.686 m2, the best one as 3331.845 m2 and the worst one as 2935.414 m2; the mean value with LIs is only 2528.864 m2, the best one as 2869.225 m2 and the worst one as 2297.590 m2. When ReaderN = 28, with GD-MRSOA-AIS, the mean value is glided down to 2737.177 m2, the best one as 3068.395 m2 and the worst one as 2436.688 m2; with LIs, the mean value is slumped down as 1670.742 m2, the best one as 1859.409 m2 and the worst one as 1532.377 m2.In addition, Sift_Function and the large effective interrogation range dues to the proposed-AIS optimization process. As a result, the deployment of eight readers with five available time slots and 10 available frequency channels is the most economical way to maximize the total effective interrogation range in 100 × 100 m2, especially using GD-MRSOA-AIS.In conclusion, GD-MRSOA-AIS could schedule multiple readers operating in fairness with lower multiple-reader interfering and large effective interrogation range, where the fairness with lower multiple-reader interfering dues to the geometric distribution of This paper refers to the multiple-reader interference problem in the multiple-reader environment (MRE) and formulates a resource allocation model with the consideration of interference avoidance in SINR under EPCGlobal C1G2 standard, where the allocable resources include available time slots and frequency channels. Based on this resource allocation model, GD-MRSOA-AIS is further proposed. In GD-MRSOA-AIS, geometric distribution replaces the uniform distribution to produce the feasible scheduling schemes, where the reader, which is interfered by large quantity of readers, has more opportunities to be allocated in an operating time slot. To optimize these feasible scheduling schemes, the artificial immune system optimization including immune clone, immune mutation and immune suppression is further introduced. During the mutation operation for antibodies, there are two optional mutation operators depending on the affinity values. According to the simulation results, GD-MRSOA-AIS could obtain an optimal and fairer readers collaboratively operating scheduling scheme, and it could output a larger total effective interrogation range with higher convergence than the state-of-the-art one.It only focuses on the scenario of multiple readers in known position with randomized tags in fixed positions, and ignores the new entrancing tags with variable population.It only solves the resource allocation problem for multiple readers scheduling to interrogate the tags in centralized MRE, but ignores the identification problem  in data transmission process.Although GD-MRSOA-AIS indeed enhances the effective interrogation range with lower interferences by fairer operating scheme, it still has shortcomings:Therefore, the next work will reconstruct a resource allocation model by considering the variable population of tags and identification problem with an enhanced scheduling-based algorithm.


The aim of this study was to investigate the associations of serum levels of neuron-specific enolase (NSE), pro-gastrin releasing peptide (ProGRP), and lactate dehydrogenase (LDH) with clinical response and survival in small cell lung cancer (SCLC) patients receiving first-line platinum-based chemotherapy.One hundred thirty-six patients with SCLC were recruited in this study. All the patients received first-line platinum-based chemotherapy. Clinical efficacy was assessed according to Response Evaluation Criteria in Solid Tumors v1.1 criteria. Serum samples were collected from SCLC patients before chemotherapy. NSE, ProGRP, and LDH levels were measured by commercial electrochemiluminescence immunoassay, enzyme-linked immune sorbent assay, and kinetic spectrophotometric method, respectively.Overall response rate was 71.3% with 97 patients who achieved complete response (CR) +  partial response (PR). NSE and LDH level declined in patients who achieved CR + PR compared with patients in stable disease (SD) and progress disease (PD). Multivariate logistic regression analysis revealed that NSE > 50.324 ng/mL, stage ED, and distant metastases were independent risk factors for patients achieving CR + PR, and chemotherapy > 4 cycles was an independent protective factor in predicting CR + PR. Receiver operating characteristic (ROC) curves presented that expression of NSE, ProGRP, and LDH are of good predicting value for patients achieving CR + PR. Patients with a higher level of NSE and LDH presented worse progression-free survival and overall survival. In addition, multivariate Cox regression analysis showed that NSE level > 50.324 ng/mL and distant metastasis were independently correlated with worse OS.Serum NSE and LDH could be promising biomarkers for predicting therapy response and survival of SCLC patients receiving first-line platinum-based chemotherapy. Regardless of these improvements in SLCL treatments, 19% to 43% patients still do not response well to platinum-based chemotherapy,,11 thus identification of convincing biomarkers for prognosis is deadly needed.Combination chemotherapy, generally 4 to 6 cycles of platinum-based and etoposide or irinotecan, is the cornerstone treatment in both LD and ED SCLC patients, especially for patients with metastatic disease. NSE, known as enolase-γ, is a dimer composed of apparently identical subunits, with high concentrations localized in neurons and neuroendocrine cells. Accumulating researches demonstrate that NSE plays critical roles in aerobic glycolysis of various tumors such as SCLC.,13 Apart from the correlation of high NSE levels and tumor mass extension, NSE levels are also reported to be frequently reduced in SCLC after chemotherapy treatment. ProGRP, a gastrointestinal hormone of the bombesin family, is the precursor for gastrin-releasing peptide (GRP) and more stable than GRP.,14 ProGRP discloses high sensitivity and specificity in diagnosing SCLC and is associated with disease stage as well as distant metastasis. As for LDH, it is a protein related to tumor metabolism and can be applied for the detection of malignancies in serum. Specifically, LDH is the key enzyme in glycolytic metabolism that stimulates the interconversion of pyruvate to lactate. In addition, several investigators found that LDH levels are elevated during cell malignant transformation in various types of cancer, including SCLC.,16 However, few reports illuminate the prognostic value of NSE, ProGRP, and LDH in SCLC patients applying first-line platinum-based chemotherapy.With neuroendocrine cellular origin, SCLC usually expresses neuroendocrine markers, including neuron-specific enolase (NSE), chromogranin A, pro-gastrin releasing peptide (ProGRP), bombesin, and lactate dehydrogenase (LDH).Our study aimed to investigate the association of serum levels of NSE, ProGRP, and LDH with clinical response and survival in SCLC patients receiving first-line platinum-based chemotherapy.22.1 This study was approved by Ethics Committee of The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, and all the participants (SLCL patients and HCs) signed the informed consents.One hundred thirty-six patients with SCLC were recruited from September 1, 2012, to December 31, 2014, at the Department of Respiratory in The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology. All the patients were diagnosed by clinical, pathological, and radiographic evidences, and no treatments were performed before joining this study. Patients less than 18, with tumor or severe infection history, lack compliance, pregnancy, or lactation were excluded. Staging was carried out according to the veterans administration lung cancer group (VALG) staging system: LD was defined as disease confined to 1 hemithorax including mediastinal lymph nodes and/or supraclavicular lymph nodes; ED was defined in those not having LD and in patients with a malignant pleural effusion.2.2All the patients received first-line platinum-based chemotherapy. Patients in LD also received radiotherapy. And patients were followed up once a month in first half year, and once every 3 months from 0.5 year to 2 years, then once every 6 months from 2 years to the last date of follow-up . The median follow-up time was 29 months.2.3Clinical efficacy was assessed according to Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 criteria as follows: CR (complete response), PR , PD (progress disease), and SD (stable disease). Overall response rate (ORR) was defined as the percentage of patients who achieved CR + PR. And progression-free survival (PFS) was calculated from the chemotherapy to time of first progression or death from any cause. Overall survival (OS) was also calculated from the chemotherapy to time of death from any cause.2.4Serum samples were collected from SCLC patients before chemotherapy. NSE was measured by commercial electrochemiluminescence immunoassay (ECLIA) using ELECSYS 2010 analyzer and reagent kits . ProGRP was determined by enzyme-linked immune sorbent assay (ELISA) using ELISA kit . The LDH activity detected by a kinetic spectrophotometric method using Model 912 biochemical analyzer .2.5P value < .05 was considered significant.SPSS 19.0  was used for statistical analysis in this study. Data were presented as mean with standard deviation, or median with one-fourth quarter to three-fourth quarter, or count with percentage. The Kolmogorov–Smirnov test was used to assess the normality of continuous data. Difference among 3 groups was determined by Kruskal–Wallis H rank sum test. Receiver operating characteristic (ROC) curve was performed to evaluate serum NSE, ProGRP, and LDH levels for predicting CR + PR by first-line chemotherapy, and univariate and multivariate logistic regression was used to analyze the factors for predicting CR + PR. In addition, Kaplan–Meier (K-M) curve and Log-Rank test was used to investigate the correlation of serum NSE, ProGRP, and LDH levels with PFS as well as OS, and univariate and multivariate logistic regression was carried out to analyze the factors that influence PFS and OS. The correlations among the levels of NSE, ProGRP, and LDH before chemotherapy were determined by Spearman test. 33.1). In the remaining 183 patients who were screened for eligibility, 19 cases were excluded: 2 patients fit for the exclusion criteria and 17 disagreed with informed consents, leading to 164 patients included. Ultimately, of the 164 included patients, 28 cases did not receive first-line platinum-based chemotherapy, resulting in 136 patients included in final analysis.During study period, 214 SCLC patients were invited at the beginning and 31 cases were not assessed for eligibility, among which 5 patients missed invitation and 26 patients declined to be invited  patients achieved CR and 95 (69.9%) patients achieved PR as listed in Table 3.3Serum level of NSE declined in patients achieved CR + PR [40.495 (21.597–70.224) ng/mL] compared with patients were SD and PD  (Table 3.4P = .002), stage ED (P = .001), and distant metastases (P = .040) were less likely to achieve CR + PR, while chemotherapy > 4 cycles (P = .029) was a promoting factor for patients achieving CR + PR. All factors with P value < .1 were subsequently included in multivariate logistic regression analysis, which revealed that a high level of NSE (P = .004), stage ED (P = .003), and distant metastases (P = .017) could independently predict that patients were less likely to achieve CR + PR, and chemotherapy > 4 cycles (P = .040) was an independent factor in predicting patients achieving CR + PR.As summarized in Table ROC curves presented that expression of NSE, ProGRP, and LDH was of good predicting value for patients achieving CR + PR with the area under curve (AUC) of 0.683 [95% confidence interval (95% CI): 0.583–0.783], 0.610 (95% CI: 0.507–0.714), and 0.639 (95% CI: 0.527–750), respectively , high level of LDH > 200 IU/L (P = .027), stage ED (P = .008), distant metastasis (P = .025), and chemotherapy cycles≤4 (P = .034) were factors in predicting worse PFS, while ProGRP (P = .526), age (P = .526), gender (P = .649), smoking history (P = .151), and tumor size (P = .240) were not correlated with PFS , LDH > 200 IU/L (P = .010), and distant metastasis (P = .017) were manifested to be independently correlated with shorter PFS  and LDH > 200 IU/L (P = .025), stage ED (P = .010) as well as distant metastasis (P = .017) were prognostic factors for shorter OS. Subsequently, factors with P value < .1 were analyzed by multivariate Cox hazard regression, which revealed that NSE level > 50.324 ng/mL (P = .019) and distant metastasis (P = .008) were independently correlated with worse OS   and LDH  was found.The NSE expression before chemotherapy was positively associated with the level of LDH pre-chemotherapy . Therefore, prognostic tools to monitor the treatment and to early assess the therapy response during first-line chemotherapy are eagerly needed to be identified, which would help to tailor and optimize disease management for SCLC patients.SCLC is an aggressive cancer, with high incidence, mortality, and unfavorable prognosis. Recently, identification of the optimal tumor makers for SCLC prognosis has been the focus of many researches. Previous studies have already presented that NSE has a potential role of mirroring the SCLC disease activity and metabolism, and then was applied to early predict insufficient response to chemotherapy.,14,15,18 As one of the most powerful prognostic markers for SCLC, NSE has been widely and preferentially used in clinical trial and routine practice.,18,19Tumor markers were known as a class of biologically active substances, which were synthesized by tumor cells and then released into the body fluids or tissues.,21 The role of NSE level in assessing the therapy response has also been characterized by other studies, a study conducted on SCLC patients elucidated a prognostic value of NSE for relapse, before which patients had achieved CR or PR to first-line chemotherapy.,23 For the prognostic value of NSE, Ebert et al discovered that patients with a decrease of NSE level had obviously better survival than those with relatively higher levels of NSE. As another tumor marker, serum LDH is elevated during cell malignant transformation.,25,26 In this present study, the results showed that high serum LDH level was correlated with unsatisfactory therapy response and poorer survival of SCLC patients, indicating that LDH is a potential marker in prognosis of SCLC in predicting the efficacy of chemotherapy and survival for SCLC patients. Numerical studies indicated that LDH expression increased with tumor progression, and the prognostic role of LDH in cancers has been reported in respectable studies.,25 Hermes et al identified LDH level as an independent predictor of mortality and morbidity fin SCLC patients under chemotherapy. LDH expression in serum was also demonstrated to be a predicting factor for therapy response and survival of SCLC patients treated with chemotherapy in other studies.–30 Our study revealed that lower serum levels of NSE and LDH in SCLC patients were associated with better therapy response and survival; those data were broadly in line with this study. In addition, high level of NSE, stage ED, and distant metastases could independently predict worse CR + PR in patients according to multivariate logistic regression analysis. Although the measurements of stages and distant metastases are relatively established method for predicting outcome of patients, there is still an additional benefit of NSE measurement over stage and distant metastases. Stages and distant metastases measurements are not applicable for all SCLC patients because the measurements are invasive, while the examination of NSE in serum is much more easy to perform on patients in clinical practice, which is conducted through collecting blood samples, when compared with the measurements of stage and distant metastases.NSE was firstly discovered in brain tissues and in amine precursor uptake and decarboxylation (AUPD) cells subsequently, while a former study has illuminated that serum NSE can be produced by SCLC tumor as well. However, the role of ProGRP in distinguishing good and poor prognosis was not revealed in our study. And many factors may be the potential roots of discrepancy, such as different treatments and clinical characteristics of patients, the varying techniques used to detect ProGRP levels, and the threshold levels of ProGRP. In addition, some researches have also previously illustrated that ProGRP had a worse sensitivity than NSE in terms of prognostic value for SCLC patients.,32ProGRP is known as a precursor of GRP and was proved to be more stable than GRP; former studies validated that alteration of ProGRP level could be a prognostic factor for clinical response, PFS, and OS of SCLC patients.Some limitations existed in our study: in this prospective single-armed study, the sample size that included 136 SCLC patients is relatively small, which means a large sample size study is needed in the future; the cut-off value of NSE and ProGRP in our study was the median value, which might result in some bias in this study; and the median follow-up was 29 months, which is a relatively short follow-up period. However, survival of SCLC patients is poor, which resulted in the difficulty in follow-up.5Our study validated that both serum NSE and LDH could be regarded as promising biomarkers for predicting therapy response and survival of SCLC patients receiving first-line platinum-based chemotherapy.


Escherichia coli, the sigma factor σ70 directs RNA polymerase to transcribe growth-related genes, while σ38 directs transcription of stress response genes during stationary phase. Two molecules hypothesized to regulate RNA polymerase are the protein Rsd, which binds to σ70, and the non-coding 6S RNA which binds to the RNA polymerase-σ70 holoenzyme. Despite multiple studies, the functions of Rsd and 6S RNA remain controversial. Here we use RNA-Seq in five phases of growth to elucidate their function on a genome-wide scale. We show that Rsd and 6S RNA facilitate σ38 activity throughout bacterial growth, while 6S RNA also regulates widely different genes depending upon growth phase. We discover novel interactions between 6S RNA and Rsd and show widespread expression changes in a strain lacking both regulators. Finally, we present a mathematical model of transcription which highlights the crosstalk between Rsd and 6S RNA as a crucial factor in controlling sigma factor competition and global gene expression.In  Proteins called sigma (σ) factors bind to E forming Eσ holoenzymes, and direct it to transcribe from specific promoters. Escherichia coli has seven sigma factors (70 (RpoD), σ38 (RpoS), σ32, σ54, σ28, σ24 and σ19. Though it was previously reported that the cellular concentration of E exceeded that of sigma factors  is the housekeeping sigma factor, directing transcription of genes essential for growth. The major alternative sigma factor, σ38 (RpoS), is present in low concentration during exponential growth, but regulates several hundred genes  supplemented with 0.5% glucose and 0.1% casamino acids was used for RNA-seq and validation. During strain construction, ampicillin or kanamycin were used at final concentrations of 100 μg/ml and 50 μg/ml respectively.Luria-Bertani broth and agar (20 g/L) were used for routine growth. M9 defined medium , mid-exponential (OD600 ∼0.8), transition to stationary (OD600 ∼1.6), stationary , and late stationary  phases of growth. RNA was extracted using TRIzol (Invitrogen), following the manufacturer’s protocol. Total RNA was treated with DNase I  according to the manufacturer’s protocol. Further precipitation of RNA and ribosomal RNA cleanup was achieved using the MICROBExpress bacterial mRNA purification Kit  according to the manufacturer’s protocol. RNA concentration was determined using a Nanodrop 2000 (Thermo Scientific) and quality was checked by visualization on agarose gels.Overnight cultures in M9 glucose were inoculated in 100 mL fresh M9 glucose to a final ODSequencing libraries were prepared using TruSeq RNA sample preparation kit v2  according to the manufacturer’s guidelines, checked for quality on an Agilent 2100 Bioanalyzer, and sequenced for 50 cycles from one end on an Illumina HiSeq1000 platform at the Centre for Cellular and Molecular Platforms, Bangalore. RNA-Seq data are summarized in Table S2. RNA-Seq reads were mapped to the E. coli K-12 MG1655 genome using BWA .qRT–PCR was carried out using specific primers to selected mRNA targets . 5 ng RNA was used for each RT-PCR reaction. TAKARA One-step SYBR PrimeScript RT-PCR kit II (RR086A) was used according to the manufacturer’s protocol, on an Applied Biosystems ViiA 7 Real-Time PCR system.70 , Mouse monoclonal antibody to σ38 , Mouse monoclonal anti-FLAG antibody , Mouse monoclonal antibody to GroEL . Bands were visualized using SuperSignal West Dura Chemiluminescent Substrate  and imaged using an ImageQuant LAS 4000 system . Band intensities were quantified using ImageJ (http://imagej.nih.gov/ij).Cells were grown as for RNA-seq. For stationary phase samples, 5 ml culture was harvested by centrifugation. For mid-exponential phase, 10 ml was harvested. Lysates were prepared and protein concentration was estimated using BCA assay . Lysates containing equal amounts of protein were loaded onto an SDS-PAGE gel. Proteins were elecroblotted onto a nitrocellulose membrane and probed with mouse primary antibody against the protein of interest followed by horseradish peroxidase-conjugated anti-mouse secondary antibody. The primary antibodies were: Mouse monoclonal antibody to RpoB , Mouse monoclonal antibody to σE. coli K-12 MG1655 genome was downloaded from NCBI (NC_000913.2). Gene coordinates were taken from RegulonDB v8.0  - (4) and (8) – (9). KNS represents the dissociation constant for non-specific binding of RNA polymerase to DNA, which we assume is equal for E, Eσ70 and Eσ38. We also assume the specific binding constants of Eσ70 and Eσ38 to their target promoters to be equal in stationary phase.The model with DNA , while 6S RNA binds to the Eσ70 holoenzyme and prevents it from binding promoters. To identify their effects on gene expression, we carried out RNA-seq to identify genes regulated by Rsd and / or 6S RNA in five growth phases.E. coli K-12 MG1655 (Wild-type), Rsd knockout (Δrsd), 6S RNA knockout (ΔssrS), 6S RNA-Rsd double knockout (ΔrsdΔssrS), and σ38/RpoS knockout (ΔrpoS) were used for RNA-seq. These had similar growth rates in M9 glucose . RNA-seq was performed in five growth phases: early exponential (EE), mid-exponential (ME), transition to stationary (TS), stationary (S), and late stationary .Table S1 lists strains and plasmids used. Five strains: rsd strain showed only 16 differentially expressed genes. These included several non-coding RNAs  which were increased two- to sixfold in Δrsd during stationary phase. Notably, 6S RNA expression was altered in Δrsd; 6S RNA was 2.3 times its wild-type level in stationary phase, but in ME phase was reduced to about half its wild-type level.We defined differentially expressed genes as genes whose expression changed >=twofold in a mutant strain relative to wild-type, with FDR-adjusted p-value < 0.05. Using these criteria, the Δrsd, we looked for smaller changes. We found that in all growth phases, genes whose expression was significantly reduced  in ΔrpoS also displayed reduced expression in Δrsd. The box plots in 2 fold change in gene expression in Δrsd relative to wild-type. ∼75% of genes whose expression was significantly reduced in ΔrpoS showed reduced expression (log2 fold change < 0) in Δrsd. Similar plots for other growth phases are in Figure S2A. This reduced expression was less than twofold in magnitude and so was not seen when searching for differentially expressed genes.As very few genes were differentially expressed in ΔP < 10−15 in all growth phases except LS) decrease in expression across hundreds of rpoS regulated genes, in all five growth phases. Second, the average overlap between the set of rpoS regulated genes in successive growth phases is only 54% - so it is not a single set of genes whose expression is reduced in Δrsd, but a different set in each growth phase. Third, the Δrsd samples showed high inter-replicate correlation in all growth phases (Table S2). Fourth, this trend of decreased expression held true when only previously reported σ38 targets . On the other hand, expression of genes controlled by constitutive σ70 target promoters , we consider them important for several reasons. First, they represent a consistent and highly significant ; however, it is extremely difficult to obtain reliable measures of small differences in protein level using western blots. We cannot be certain based on this experiment whether the reduced expression of σ38 targets in Δrsd is due to reduced σ38 protein, reduced E-σ38 association, or both. We attempt to address this question theoretically later.Thus, the Rsd knockout behaved like a σ70 - sequestering 6S RNA play in gene regulation? Is its function similar to that of the σ70-sequestering Rsd? Our RNA-seq showed that the 6S RNA knockout (ΔssrS) was very different from the Rsd knockout. To begin with, it showed >=twofold differential expression of 447 genes in total.What role does the EσssrS in successive growth phases, even in the two stationary phase time points. Only a few genes were differentially expressed in ΔssrS throughout growth, particularly fau (ygfA), which is downstream of 6S RNA in the same operon. fau expression was increased when 6S RNA was overexpressed in a wild-type background , indicating that this is at least partly a regulatory effect of 6S RNA and not merely a polar effect.artM, artI, hisP, hisQ, hisJ, hisM, tdcC) and amino acid biosynthesis  was increased in ΔssrS, while expression of genes involved in stress responses  was reduced. On the other hand, in LS phase, genes involved in global transcriptional regulation  and the TCA cycle  were upregulated. Thus, the physiological function of 6S RNA appears largely growth phase-dependent; nevertheless, there are certain patterns throughout growth.During exponential phase, expression of several genes for amino acid transporters . This was not due to reduced σ38 protein, as western blots in stationary phase showed that the ΔssrS strain had higher σ38 protein than the wild-type . On the other hand, expression of genes under constitutive σ70 promoters was slightly increased in the ME, TS and LS phases .Like 70  was reduced in ΔssrS, and the magnitude of reduction increased with growth phase . For instance, expression of th phase . Reducedlymerase , consistcrl expression is increased in ΔssrS, and the magnitude of this effect increases with growth phase. As with the effect of reducing RNA polymerase synthesis to compensate for the loss of 6S RNA, increasing σ38 protein and Crl may be a means to compensate for reduced Eσ38 activity in ΔssrS bacteria.6S RNA also represses some genes in a dose-dependent manner. rsd was not differentially expressed in ΔssrS. To check if 6S RNA regulated Rsd post-transcriptionally, we added a 3xFLAG tag to the C-terminal of the Rsd protein, as in previous studies  forming holoenzymes (Eσ70 and Eσ38). Holoenzymes initiate transcription from target promoters (P70 and P38), releasing the sigma factor. The elongating RNA polymerase (Ee70 and Ee38) transcribes until released. Holoenzymes and E also bind DNA non-specifically. We focus on the steady state of this model, determined by equations (1) - (4) and (8) – (17) in Methods.70 and Eσ38 in the absence of DNA. This is represented by the shaded area in 70 and σ38. Each value of Rsd on the x-axis corresponds to a separate ’run’ of the model where we compute the steady-state for those parameter values, before moving on to the next Rsd value. We predict that as Rsd is increased, it sequesters σ70, reducing Eσ70 formation. This allows more E to bind σ38, increasing the formation of Eσ38, consistent with previous predictions of Rsd function  in the Rsd knockout. We did not include this in the model due to lack of quantitative data on oxyS; however, it is possible that a small reduction in σ38 protein levels, perhaps due to increased oxyS, may contribute to reduced σ38 activity in the Δrsd strain. However, it is difficult to confirm this.We also observed a 2.4-fold increase in 70, reducing the amount of E available to bind to both sigma factors and thus inhibiting formation of both holoenzymes. This decreases the rate of transcription by both holoenzymes . However, there is still relatively low overlap in the list of 6S RNA regulated genes (46 genes). This is likely because of differences in time points and media. Even within our dataset, there is little overlap between genes regulated by 6S RNA at different time points. It seems that the 6S RNA regulon varies greatly under different conditions. This supports a model where 6S RNA acts as a background-level regulator operating on RNA polymerase, with gene-level outcomes depending strongly upon cellular environment; this could involve DNA topology, transcription factors, and other RNA polymerase-binding factors, all of which vary with growth phase (in vitro transcription experiments testing whether the ability of 6S RNA to regulate known targets is affected by the presence of other regulators in the medium.6S RNA is more complex, regulating expression of >400 genes; however, we did not observe associations between promoter sequence and 6S RNA susceptibility as previously reported (th phase . Regulat38 during stationary phase. It was unknown whether this was a direct effect of 6S RNA, allowing σ38 to compete more effectively for E, or indirect, via a trans-acting factor important for σ38 activity. However, another study (38 globally, from early exponential to stationary phase, and show mathematically that this is extremely unlikely to be a direct effect of sequestration. We show that 6S RNA increases Rsd protein level and suggest that Rsd is primarily responsible for 6S RNA’s effect on Eσ38 activity.Previous work using individual promoters  had suggssrS strain, where the cell reduces RNA polymerase expression to compensate for 6S RNA loss, and increases σ38 and possibly Crl to compensate for reduced Eσ38 activity. Apart from these two, increased ppGpp may also have such a compensatory role during TS phase, while in LS phase, the 6S RNA knockout has higher expression of ppk, responsible for synthesis of polyphosphate - which activates transcription by Eσ38 (70 and Eσ38 (38 expression (It has been asked, given 6S RNA’s function as a global regulator, why its deletion does not cause a growth defect. Our data, along with others ( by Eσ38 . In statWe see that 6S RNA and Rsd regulate each other’s expression, and control each other’s effect on gene expression; finally, we report that 1780 genes across 5 growth phases—almost 40% of the genes in the cell—are differentially expressed in the 6S RNA-Rsd double knockout but not in the single knockouts added together. This provides direct evidence that 6S RNA and Rsd have non-additive effects on gene expression, since the single knockouts cannot explain the widespread gene expression changes observed in the double knockout. Previous studies have only examined single knockouts; this underscores the importance of studying 6S RNA and Rsd as a unit that controls global RNA polymerase activity.Given that 6S RNA homologs are widespread in bacteria, co-occurring with Rsd and with other RNA polymerase regulators such as the actinobacterial RbpA, and many species have two or three 6S RNA homologs with different expression patterns and potentially different binding partners (


Plasmopara viticola. Thisdisease poses a serious threat wherever viticulture is practiced. Wild Vitisspecies showing resistance to P. viticola offer a promising pathway to developnew grapevine cultivars resistant to P. viticola which will allow reduced use ofenvironmentally unfriendly fungicides. Here, transmission and scanning microscopy was usedto compare the resistance responses to downy mildew of three resistant genotypes of V.davidii var. cyanocarpa, V. piasesezkii and V. pseudoreticulataand the suceptible V. vinifera cultivar ‘Pinot Noir’. Followinginoculation with sporangia of P. viticola isolate ‘YL’ on V.vinifera cv. ‘Pinot Noir’, the infection was characterized by a rapidspread of intercellular hyphae, a high frequency of haustorium formation within thehost’s mesophyll cells, the production of sporangia and by the absence of host-cellnecrosis. In contrast zoospores were collapsed in the resistant V.pseudoreticulata ‘Baihe-35-1’, or secretions appeared arround stomataat the beginning of the infection period in V. davidii var. cyanocarpa‘Langao-5’ and V. piasezkii ‘Liuba-8’. The maincharacteristics of the resistance responses were the rapid depositions of callose and theappearance of empty hyphae and the plasmolysis of penetrated tissue. Moreover, collapsedhaustoria were observed in V. davidii var. cyanocarpa ‘Langao-5’ at5 days post inoculation (dpi) and in V. piasezkii ‘Liuba-8’ at 7dpi. Lastly, necrosis extended beyond the zone of restricted colonization in all threeresistant genotypes. Sporangia were absent in V. piasezkii‘Liuba-8’ and greatly decreased in V. davidii var. cyanocarpa‘Langao-5’ and in V. pseudoreticulata ‘Baihe-35-1’compared with in V. vinifera cv. ‘Pinot Noir’. Overall, theseresults provide insights into the cellular biological basis of the incompatibleinteractions between the pathogen and the host. They indicate a number of severalresistant Chinese wild species that could be used in developing new cultivars having goodlevels of downy mildew resistance.The downy mildew disease in grapevines is caused by  This diseaseis one of the most serious threats faced by viticulture in most areas where grapes aregrown. The pathogen came from wild Vitis species of North America was firstreported in Europe in 1878.2 It is believed tohave been introduced to Europe on cuttings of American wild grapes, imported for use asbreeding stock for Phylloxera resistance.2 Since then, it has become widespread and is now a majorproblem.3Grapevine downy mildew is caused by the obligate biotrophic oomycete,P. viticola attacks all green parts of grapevines including the leaves, theclusters and young fruit.4 In warm, humidweather, the asexual sporangia release four to eight zoospores.5 When a zoospore encounters a stoma, it attaches and encysts. Nextit forms a germ tube that penetrates the substomatal cavity. Subsequently, this germ tubeswells into an infection vesicle.6 A primaryhypha appears from an infection vesicle and quickly develops branches andhaustoria.7 After an incubation period ofseveral days (sometimes in as few as 4 days),5sporangiophores emerge through the stomatum and form sporangia.8 At the end of autumn, numerous oospores form within fallen leavesand berries allowing P. viticola to overwinter.9Vitis species and cultivars vary in resistance toP. viticola.12 Generally, V. viniferacultivars such as ‘Pinot noir’ are susceptible to P. viticola whilemost Vitis species from North America are highly resistant,13 for example, V. rupestris and V.riparia,14 while Muscadiniarotundifolia is immune.15 Some Chinesewild Vitis genotypes such as V. pseudoreticulata‘Baihe-35-1’ and V. davidii var. cyanocarpa‘Langao-5’ are also resistant to P. viticola, while V.piasezkii ‘Liuba-8’ is highly resistant.17It has been reported that P. viticolainfection in grapevine at the histological and ultrastructural levels, including callosedeposition in stomata,18 lignification,19stilbenic phytoalexin production,21 hydrogen peroxide (H2O2)accumulation 23 and hypersensitive reactions.24 The ultrastructural response to downy mildew varies among theresistant species. Using KOH-aniline blue fluorescent staining, Gindro et al.observed callose and secretions in the resistant V. vinifera cv.‘Solaris’ but not in the susceptible V. vinifera cv.‘Chasselas’.8 Haustoria andhyphae were found to be degenerated in V. riparia (var. Gloire de Montpellier)and M. rotundifolia cv. ‘Carlos’25 using transmission electronmicroscopy and these reactions may reduce pathogen growth.26 In addition, trichomes and bristles, cuticular waxes, density ofstomata and internal cuticular rims may be related to resistance to P.viticola.28 In a previous study, the reaction of Chinese wild Vitisspecies to P. viticola was elucidated at the histological level.16 In this study we aim to compare, at the ultrastructurallevel, the characterization of the pathogen development and host response duringincompatible and compatible interactions between isolate P. viticola‘YL’ and three resistant Chinese wild Vitis species and onesusceptible V. vinifera cultivar.Many studies have reported on the mechanisms of resistance against P. viticola isolate ‘YL’ (Yang Lingtown) was collected from an infected grapevine leave  in the Grape Repository of NorthwestA&F University, Yangling, Shaanxi, China. The method for isolating P.viticola ‘YL’ refers to Wong and Wilcox.29 Briefly, P. viticola was purified for three times bysingle sporangiophore transfer from infected leaves, then the isolate was propagatedweekly on detached leaves of V. vinifera cv. ‘Pinot Noir’ in90 mm Petri dishes  on wet filter paper and incubated ina controlled environment under a photoperiod (temperature) of 16 h light(22 °C) and 8 h of darkness (18 °C) and 80% relativehumidity.The V. vinifera cv.‘Pinot Noir’, V. pseudoreticulata ‘Baihe-35-1’,V. davidii var. cyanocarpa ‘Langao-5’ and V. piasezkii‘Liuba-8’ were obtained from the Grape Repository of Northwest A&FUniversity, Yangling, Shaanxi, China.16 Theleaf surfaces were sterilized using bleach (0.01%) and then rinsed three times insterile distilled water. Leaf discs (10 mm diameter) were obtained with a corkborer. The abaxial surfaces were inoculated with 50 μl drops of an aqueoussuspension of 5×104 sporangia per ml and placed on wet filter paper in90 mm Petri dishes. The control groups of leaf discs were inoculated with50 μl drops of sterile distilled water. Incubation conditions were asdescribed above.The third and fourth fully-expanded leaves from the apex of m phosphate buffered saline (pH 6.8) for 10 min each anddehydrated in a graded series of aqueous ethanol solutions —each step for 15 min. Finally, samples were soaked inisoamyl acetate for 30 min, critical point dried in CO2 and coatedwith gold. Mounted samples were viewed with an Hitachi S-4800  scanningelectron microscope at 10 kV.Samples of leaf discs were collected at 0.5 day post inoculation (dpi), and at 1, 3, 4,5, 6, 7, 8, 9, 10 and 11 dpi. Samples were cut into 5×5 mm pieces, fixed in4% glutaraldehyde at 4 °C overnight, rinsed four times with0.1 m phosphate buffered saline (pH 6.8) four times for10 min each. The samples were then fixed in 1% osmium tetroxide (OsO4)for 2 h, dehydrated in a graded series of ethanol (as above), and infiltratedwith London Resin Company Ltd (LR) White resin . This involvedinfiltration in a series of mixtures of acetone and LR White resin in the proportions,3:1, 1:1 and 1:3 (vol/vol) for 6 h each, then a final infiltration in pure resinfor 72 h. Finally, the samples were embedded in pure LR White resin andpolymerized at 55 °C for 48 h.Samples (2×5 mm) of leaf discs were taken at 3, 5 and 7 dpi, fixedimmediately in 4% glutaraldehyde at 4 °C overnight and washed with0.1 Semi-thin sections (1 μm) of samples were cut with a glass knife andstained with 0.3% aqueous toluidine blue in 1.89% sodium tetraborate. Semi-thin sectionswere examined in bright-field microscopy using an Olympus BX 51  to focuson infected sites. Ultra-thin sections (90 nm) were cut with a diamond knife,collected on copper grids, stained with uranyl acetate and lead citrate and observed bytransmission electron microscopy 1230 (JEOL)  at80 kV.30 Aqueous suspensions of 5×104sporangia per ml were confirmed using a hemocytometer for calibration.Twelve leaf discs were inoculated as described above. At 9 dpi, sporangia on each leafdisc were shaken into a 2 ml plastic tube containing 1 ml of distilledwater. The number of sporangia in the water was measured by turbidimetry with aspectrophotometer at 400 nm by the method of Gindro and Pezet.et al.31 Thepercentage of infected stomata  was calculated according to Yu et al.7 using a fluorescence microscope .16At 1 dpi, 12 leaf discs were stained with KOH-aniline blue by the procedure ofDíez-Navajas P⩽0.05. All calculations were carried outusing SPSS 13.0 software .Each experiment was carried out in triplicate. Data were analyzed by analysis ofvariance to detect any statistically significant differences. Least significantdifferences are reported at Initially, we used bright-field microscopy for cytological observation. The hyphaestained with toluidine blue showed vacuolation and contrasting colors of the cell walland cytoplasm in all samples. In ‘Pinot Noir’ at 3 dpi, hyphae werewidespread and closely attached to the cell wall of mesophyll cells and filled theintercellular spaces of the leaves. A high frequency of pyriform haustoria was observed,breaking through the mesophyll cell walls and with some haustoria reaching the palisademesophyll . In ‘BaiTo provide a more comprehensive insight, we carried out an ultrastructural study. At0.5 dpi, encystment of zoospores was observed on the stomata of all genotypes Figure 5.At 3 dpi, hyphae in ‘Pinot Noir’ were characterized by normalultrastructure with numerous vacuoles . In‘BaiAt 5 dpi, in ‘Pinot Noir’, the cytoplasmic membrane of hyphae andhaustoria were closely attached to the cell wall of mesophyll cells and with homogenouscell of the leaves . In‘BaiAt 7 dpi, in ‘Pinot Noir’ typically pyriform haustoria showing theaccumulation of electron-dense material, continuous with the extra-haustorial matrixwere observed in host cells and the hyphae were characterized by the presence ofnumerous mitochondria and vacuoles . In‘BaiIn ‘Pinot Noir’ and ‘Baihe-35-1’, new sporangiophoresemerged through the stomata at 4 and 5 dpi, respectively,  and 3d. Sporangiophores and sporangia were fully developed in ‘Pinot Noir’ at 5dpi . For ‘LaAt 1 dpi, infected stomata with substomatal vesicles were observed in all genotypes. The per2, on‘Baihe-35-1’ it was 13.67 sporangia per mm2 and on‘Langao-5’ it was 12.10 sporangia per mm2  when germ tubes of encysted zoospores penetratestomata.8However, for the partially resistant genotypes, a defense response appears only when thefirst haustoria have contacted the mesophyll cells.33 In this study, zoospores were collapsed in‘Baihe-35-1’ and stomata surrounded with secretions appeared in‘Langao-5’ and ‘Liuba-8’ at 1 dpi. This would seem to indicatethat the restriction of P. viticola occurred very rapidly—within24 h. This observation is similar to that reported by Gindro et al. and Yuet al.8 The key stages to which to distinguish resistance and susceptibiltyto P. viticola are zoospore infection and haustorial formation.7 At 1 dpi, substomatal vesicles with primary hyphae wereobserved in both susceptible and resistant genotypes.33 After 1 dpi, the hyphae of P.viticola expand rapidly and branch in the susceptible genotypes, while in theresistant genotypes, most hyphae branch slowly or remain unbranched.5 In this study, P. viticola isolate‘YL’ successfully infected both susceptible and resistant genotypes whichfurther supports earlier findings.33However, the percentage of infected stomata and the scanning electron microscopeobservations both indicate that the infection rate of zoospores was significantly reducedin ‘Baihe-35-1’ and ‘Langao-5’ and greatly reduced in‘Liuba-8’.Stomata has key roles during 34 and has been reported in resistance to many fungi, such as to rust,downy mildew and powdery mildew.37 It is thought thatcallose deposition may limit or impede pathogen growth and block nutrient uptake from thehost cell by encasing haustoria.34 In our study, callose material was not observed in‘Pinot Noir’; however, callose deposition was observed in the threeresistant genotypes. The growth of P. viticola hyphae was slowed down so that thetimes required by the sporangiophores to emerge were increased and the sporangialdensities in the three wild genotypes were reduced. These results are consistent withthose of previous studies.38Callose deposition is a host-cell defense mechanism25 Extensive vacuolation and degenerate hyphae with deposits ofelectron-dense material are the result of altered biosynthesis in the pathogen cell wallafter treatment with the fungicide Mandipropamid.26 Similar results have also been described in P. viticolaafter treatment with diketopiperazines extracted from Alternaria alernata39 and in P. viticola coupled withviral infection.40 In ‘Langao-5’and ‘Liuba-8’, empty hyphae were observed as early as 5 dpi while in‘Baihe-35-1’ enlarged vacuoles were observed in hyphae and haustoria at 7dpi, indicating the hyphae were degenerate. However, in ‘Pinot Noir’, thenumerous mitochondria observed in hyphae and haustoria were covered with anextra-haustorial matrix by 7 dpi, indicating that the pathogen was viable and had highmetabolic activity.41Empty hyphae or enlarged vacuoles have been observed in older hyphae including haustoriawhile young hyphae have relatively few vacuoles.42 Abnormalor collapsed haustoria have been reported in incompatible interactions betweenArabidopsis thaliana and Peronospora parasitica,34 resistant cv. ‘IRAC 2091’(Gamaret×Bronner) interaction with P. viticola10 and P. viticola infected grapevine leaves after treatmentwith diketopiperazine extracts39 or sulfatedlaminarin (PS3).44 Collapsed haustoria were observed in ‘Langao-5’ at 5dpi and in ‘Liuba-8’ at 7 dpi which is consistent with the earlier research,referred to above. This suggests these haustoria are unable to take up nutrients from thehost cell.Mature haustoria may function as a site of molecular exchange of effectors and nutrientsbetween the host cell and pathogen.P. viticola structureswhen grapevine leaves are treated with aqueous solutions of Cu(OH)2 26 Plasma membranes of hyphae detached from the cell wall were observedin ‘Langao-5’ at 7 dpi which also showed extended lysis according toToffolatti.26 Plasmolysis was observed in‘Langao-5’ at 7 dpi and in ‘Baihe-35-1’ at 5 dpi and 7 dpiwhich is presumably a response by the host cell when exposed to hyperosmoticstress.45Previous studies have shown that plasmolysis occurs in Vitis species, including the three genotypes mentionedabove, showed complete immunity to P. viticola.46 In addition, ‘Liuba-8’ and V. labrusca‘Beaumont’ exhibited the same level (highly resistant) of resistance toP. viticola according to Wan et al.17 In this study, although the sterile sporangiophores emerged at 11dpi, sporangia were not observed in the highly resistant genotype ‘Liuba-8’.This shows that the pathogen cannot complete its life cycle in ‘Liuba-8’. Asimilar effect was described in resistant V. rupestris 66 h postinoculation, when unbranched and long sterile hyphae emerged from stomata.5 Also, necrotic spots were evident to the naked eye, onthe leaves of three wild genotypes which is consistent with Liu etal.,16 and could be associated with ahypersensitive reaction.24 The necrotic zone mayprevent hyphal extension. Evaluation of sporangial density has been widely used forestimation of resistance to P. viticola in grapevines.47 Production of sporangia can be the source of secondary infections.In this study, sporangia were not observed or detected in ‘Liuba-8’inferring that the chances of secondary infection in ‘Liuba-8’ were verymuch reduced. In ‘Baihe-35-1’ and ‘Langao-5’, the resistancereactions only delayed the growth of the pathogen and sporangia can be detected butnumbers were limited, compared with in ‘Pinot Noir’.None of the Chinese wild 49 In this study, no clearrelationships between susceptibility to P. viticola isolate ‘YL’and these ampelographic characters could be found (48Ampelographic characteristics such as erect and reclining trichomes, inner cuticularrims, waxes, structure of epidermis and mesophyll and stomatal density can act as physicalbarriers to zoospore infection at early stages.be found , which iP.viticola isolate ‘YL’ were: irregular haustoria, empty hyphae,callose depositions and plasmolysis in resistant host cells. These results provideinsights into the mechanisms of resistance in a number of resistant Chinese wildgenotypes. These have important potential as germplasm resources having resistance toP. viticola and have possible value in the development of new, P.viticola resistant, grape cultivars. Although the mechanisms of inhibition ofP. viticola development in resistant grapevines remain not fully understood,further work will focus on the molecular mechanisms of these responses and on identifyingresistance genes in these genotypes.Differences in response between resistant and susceptible grapevine genotypes to


Isochrysis are a good producer of natural docosahexaenoic acid (DHA). To better understand the patterns of DHA accumulation and distribution, two Isochrysis strains, CL153180 and CCMP462, were evaluated in this study. In a batch culture, CL153180 showed a decline in DHA content while CCMP462 exhibited a progressive increase during the late growth period when nitrogen was almost exhausted. In response to nitrogen deficiency (ND), both strains showed a considerable increase in neutral lipids (NL) at the expense of glycolipids (GL) but had little variation in phospholipids (PL). In CL153180, the DHA percentage of NL decreased gradually upon ND, while that in CCMP462 increased progressively to 21.4% after 4 days of ND, which is around 5-fold higher than CL153180. Accordingly, in contrast to CL153180 that stored DHA predominantly in GL, CCMP462 accumulated DHA mainly in NL in late days of ND. Taken together, we proposed a working model for the differential DHA partitioning patterns between two Isochrysis strains: for CCMP462, the degradation of GL released free fatty acids including DHA, which was incorporated into NL upon ND; whereas for CL153180, the released DHA from GL might not be incorporated into NL, and, consequently, might be subject to β-oxidation for degradation.The marine microalgae  As an omega-3 long-chain polyunsaturated fatty acid, docosahexaenoic acid (DHA), represents an essential substance for human metabolism and provides important physiological regulatory functions. DHA is a vital component of the brain cell membrane and retina, directly involved in the formation and development of brain cells for thinking and consolidating memory in fetuses and infants . The conSchizochytrium mangrovei [Schizochytrium limacinum [Aurantiochytrium sp. [Crypthecodinium cohnii [Isochrysis sp. [Isochrysis sp. are regarded as a good candidate. In addition to the high DHA content, they also possess the following advantages: (1) fast growth rates; (2) easy extraction due to the lack of a cell wall; and (3) higher levels of antioxidants, which helps to avoid oxidative decomposition during the extraction process [Cold-water oceanic fish oils are rich in DHA and are currently the main source of DHA for human use. Fish is unable to de novo synthesize DHA but obtains it via bioaccumulation in the food chain. However, fish oil-derived DHA has its intrinsic disadvantages, such as declining supplies, an unpleasant odor, and difficulties in controlling the quality of fish oils , which dangrovei , Schizocimacinum , Aurantirium sp. , Crypthem cohnii ,11,12 anysis sp. . Among t process ,15. Isochrysis strains from public algae collection centers, but lacked the time course comparison with respect to DHA accumulation and partitioning in different lipid classes. In this study, two Isochrysis strains, namely, CCMP462 and CL153180, were comparatively examined in a time course manner under both nitrogen-replete and nitrogen-depleted conditions. The results indicated the important role of nitrogen availability in affecting DHA synthesis and revealed distinct patterns of DHA accumulation and partitioning into neutral lipids between these two algal strains. Our data provide insights into future engineering of Isochrysis for improved production of DHA.Liu et al.  conducte−1. After 10 day of culturing (continuous illumination: 100 µmol·m−2·s−1), the biomass reached over 3 g·L−1, which was higher than previous reports and may be explained by the difference in illumination. Cai et al. [Isochrysis galbana 8701 with continuous illumination at an irradiance of 72 µmol m−2·s−1, the biomass concentration reached 1.17 g·L−1. Yoshioka et al. [−2·s−1, the biomass concentration of Isochrysis galbana after 6 day of culture increased to 1.09 g·L−1. According to a report by Liu et al. [Isochrysis galbana is proportional to illumination in the irradiance range of 30–120 µmol m−2·s−1.As indicated in i et al.  reportedu et al. , biomassIsochrysis strains were quite similar, both reaching up to 25–26% of the dry algal cell weight. According to previous reports, the overall lipid contents of Isochrysis generally account for 18–34% of the dry weight [−1·day−1 within 10 day of culturing, while the lipid productivity of CCMP462 was 79.61 mg·L−1·day−1.y weight ,20. As f−1 to 58.46 mg·L−1, while for CL153180 the DHA output started decreasing to 43.03 mg·L−1 from day 6  was reached on day 4, followed by a decrease to 11.9% from day 4 to day 10 A. Calculom day 6 C. It is Isochrysis of about 100 mg·L−1 would be exhausted within 4–6 day of culturing. In the present study, a similar scenario was observed: the initial nitrogen content in the F/2 culture medium was 120 mg·L−1 and was nearly depleted within 4–6 day of culturing, which was closely associated with the turning point in DHA accumulation between the two strains. Therefore, we proposed that nitrogen deficiency (ND) stress may be an external factor inducing the different DHA accumulation patterns between CCMP462 and CL153180. Further experiments under ND conditions were conducted to verify this hypothesis.In a batch culture, the extension in incubation time will gradually deplete nutrients in the culture medium. Of all the nutrients, nitrogen is the most important one, closely associated with the lipid synthesis in microalgae. According to a report by Liu et al. , an init−2·s−1, CL153180 and CCMP462 were cultured for 4 day under ND conditions. The two microalgae possessed similar overall lipid contents at the beginning of the experiment. The lipid content of CL153180 increased slightly from 23.5% to 26.2% within 4 day . Simionato et al. [Nannochloropsis gaditana were more likely to be converted for the synthesis of NLs. From data obtained in this study, both CL153180 and CCMP462 preferred to convert GLs to NLs under ND conditions. Berges et al. [Under a continuous light illumination of 100 µmol photo min 4 day A. The coin 4 day B,C. Thiso et al.  reporteds et al.  emphasizIn order to better examine the dynamic changes in oil in algal cells, Bodipy staining and transmission electron microscopy were performed to observe the lipid accumulation and cell structure changes under ND in CL153180 and CCMP462. As ND was prolonged, both algal cells maintained complete cell morphology with a gradual decrease in space occupied by the chloroplast. Additionally, the number and volume of oil droplets in the cells increased significantly A,B. TranIsochrysis galbana is mainly concentrated in GLs [Nannochloropsis gaditana under ND conditions. Using eicosapentaenoic acid  as a signaling molecule, the change in EPA content was detected, and it was discovered that TAG synthesis mainly relied on the de novo synthesis of fatty acids, which was accompanied by the transfer of EPA from polar lipids such as monogalactosyl diglyceride (MGDG) and digalactosyl diglyceride (DGDG) to NLs. Regardless of the sources of fatty acids, acyltransferases are needed to incorporate them into NLs (mainly TAG) [Isochrysis strains employ fatty acids recycled from GLs for the synthesis of NLs, but it is likely that CCMP462 utilized DHA while CL153180 did not (acyltransferases lack activity on DHA), leading to the differential DHA partitioning into NLs between the two strains d in GLs ,28. For d in GLs  explorednly TAG) ,30,31. I strains .The ratio of DHA to the dry weight of the algal cells in CL153180 and CCMP462 C,D was aΔ6,9,12,15 from C18:3Δ9,12,15. Petrie et al. [Micromonas pusilla, which showed higher activity towards C18:3Δ9,12,15 as a substrate than C18:2Δ9,12, thereby resulting in an increase in the contents of EPA and DHA (products of omega-3 pathway). Therefore, we hypothesized that the Δ6-desaturase activity in CCMP462 may be enhanced under ND conditions, which promotes the conversion efficiency from C18:3Δ9,12,15 to C18:4Δ6,9,12,15, ultimately leading to an increase in DHA content. In fact, there have been some reports demonstrating the response of Δ6-desaturases to nitrogen signals, and the mechanisms may be different [Isochrysis aff. galbana as a study subject and found that the response of Δ6-desaturase was positively related to ND. It was also hypothesized by Feng et al. [Myrmecia incisa that Δ6-desaturase was negatively correlated with ND. Whether the differences in the response of Δ6-desaturase to nitrogen deficiency in CL153180 and CCMP462 are species-specific requires further investigation.The above results demonstrated that the NLs in these two algae were supplied with DHA from different origins under ND conditions. As a result, we further examined the changes in fatty acid profiles including DHA . After 4e et al.  reportedifferent . Huerlimifferent  selectedg et al.  that ND g et al.  found duIsochrysis CCMP462 (CCMP462) was obtained from Provosoli-Guillard National Centre for Culture of Marine Phytoplankton. Isochrysis 153180 (CL153180) was purchased from the Carolina Biological Supply Company. For maintenance, both strains were cultured in 250-mL Erlenmeyer flasks containing 100 mL F/2 medium and 25 g·L−1 sea salt. Cultures were kept at 22 °C with continuous illumination of a low light (20 μmol·m−2 s−1), shaken by hand once a day.−1 N) and grown at 22 °C, aerated with 1.5% CO2 enriched air (compressed air and CO2 are mixed at a ratio of 100:1.5), and illuminated with continuous light of 100 μmol·m−2 s−1. Sterile water was replenished every day before sampling to avoid the effect of evaporation. The cultures in late exponential growth phase were inoculated into new column PBRs with a starting cell density of 0.3 g·L−1. For nitrogen deficiency (ND) experiments, the same inoculation was put into the nitrogen-free F/2 medium for 4 days before being harvested. Algal cultures were inoculated into column photobioreactors  containing 100 mL modified F/2 medium (120 mg L4HCO3. Cells on the filter paper discs were dried at 100 °C in an oven until constant weight and were subsequently cooled to room temperature in a desiccator before weighing. Samples were ashed at 500 °C for 2 h in a muffle furnace to obtain ash-free dry weight (AFDW). Biomass productivity was calculated on an AFDW basis.The optical density (OD) of culture was measured at 750 nm with a 1.5 cm light path cuvette in a HACH DR 2700 spectrophotometer. Culture suspension (5–10 mL) was filtered through a pre-dried Whatman GF/C filter paper (1.2 μm pore size) and washed twice with 10 mL 0.5 M NHv/v/v), and then vortexed for 15 min. The collected samples were centrifuged at 4000 rpm for 15 min and then the lower phase was collected into the brown tubes. The extracts were measured gravimetrically until dried to a constant weight with nitrogen gas. Dry lipid extracts were re-suspended in chloroform for immediate use or stored at −20 °C under nitrogen for later use.The extraction of total lipids was carried out in accordance with the modified method described by Bligh and Dyer . ApproxiTotal lipid extracts were further fractionated into neutral lipids, glycolipids, and phospholipids on silica cartridges  by sequential elution with chloroform, acetone, and methanol, as previously described . The quaApproximately 1 mL of culture solution was centrifuged at 12,000 rpm for 2 min and the supernatant was discarded. Cells were stained with 1 mL Bodipy fluorescent dye  and incubated in darkness at 25 °C for 10 min. The samples were examined using a Confocal Laser Scanning Microscope  with an excitation wavelength of 490 nm and emission wavelength of 515 nm.Isochrysis. Fresh samples were fixed with 4% paraformaldehyde and 0.5% glutaraldehyde at 4 °C for 4–12 h. The supernatant was removed and mixed with 2–5 µL egg albumen in a 15 mL-centrifuge tube. The collected algal cells were incubated with 0.5% osmic acids in 0.1 M PBS at 4 °C for 1 h. The samples were dehydrated for 10 min with ethanol and infiltrated at 25 °C with a mixture of epoxy propane and Epon812. Cells were aggregated within an aggregator . After drying, thin sections were stained with uranyl acetate and lead for 5 min. Samples were observed under a JEOL 1230 microscope .Transmission electron microscopy (TEM) was applied to determine the subcellular structures of TM-2560 Silica Capillary Column (100 m × 0.25 mm × 0.2 um film thickness). The program was as follows: the initial temperature was maintained at 130 °C for 5 min, ramping at 4 °C min−1 to 220 °C for 12 min and 20 °C min−1 to 240 °C for 8.5 min. The injection volume was 1 µL. DHA, as well as other fatty acids, were identified by comparison with the retention time of the validated standards .Fatty acid methyl esters (FAMEs) were prepared by transesterification of freeze-dried cells or individual lipids. Transesterification was conducted using 4% sulfuric acid in methanol at 85 °C for 1 h . FAMEs wAll experiments were determined in biological triplicate to ensure the reproducibility. Experimental results were obtained as the mean value ± SD. Isochrysis strains, CCMP462 and CL153180, showed differential patterns of DHA accumulation and partitioning into lipid classes under both nitrogen-replete and nitrogen-depleted conditions: in CCMP462, DHA increased and was enriched in NLs, while in CL153180, DHA dropped considerably without enrichment in NLs. Both strains accumulated NLs at the expense of GLs, but it is likely only CCMP462 can utilize GLs-derived DHA for the synthesis of NLs (mainly TAG), leading to the enrichment of DHA in NLs. In CL153180, the DHA released from GLs, due to its inability to be incorporated into NLs, is subject to β-oxidation for degradation. Taken together, our data provide insights into the DHA accumulation pattern and indicate that CCMP462 is superior to CL153180 for DHA production under batch culture conditions.The two


The data presented here were originally collected for the research project “CT-Scan processing and analysis in patient with breast cancer after radiotherapy”. Also, it reported in our study “Prediction of Lung Tissue Damage by Evaluating Clinical and Dosimetric Parameters in Breast Cancer Patients”   Specifications TableValue of the data•Raw data can be reprocessed using algorithms and other procedures in future research in the study area.•The data presents the full-information  for 52 subjects with breast cancer.11.1In this prospective analysis 52 patients  ages 34 to 71 years, (mean age: 47 years) with stages II, III breast cancers who were referred to Mahdieh radiotherapy center in Hamedan of Iran between February to August 2015 were included 1.2Radiotherapy of the patients was done using 6-MV and 15-MV photon beams produced by a linear accelerator of electron . Before radiotherapy, patients were immobilized using a breast board in the supine position while both arms were expanded over the head. CT images were obtained using a single-slice CT-scan unit  transverse slices with thickness of 8 mm. Treatment planning of radiation therapy based on the CT-scan slices for the patients was performed using the Core-PLAN  treatment planning system (TPS) The prescribed dose to the PTV was 50 Gy in 25 fractions. A number of 11 patients (6.6%) received five more fractions as a boost using 6 MV or 15 MV photon beams or 15 MeV electron beam to the tumor bed. All patients treated with tangential opposed fields, with or without an anterior supraclavicular field; however, 6 patients (6.3%) had internal mammary node (IMN) radiation field using photon or electron beams in addition to tangential and/or supraclavicular fields. Post axillary field was used in 9 patients (4.5%), too. The planning goals were to cover 95% of the target volume with 100% of the prescription dose and to keep the critical structure doses at or below known tolerance limits 1.3Pulmonary function parameters were assessed using a spirometry System in the Shahid Beheshti hospital in Hamedan, Iran, according to the American Thoracic Society recommendation Spirometry.mat.All of these pulmonary function tests were accomplished before and after completion of Radiotherapy, 3 and 6 months afterwards and were examined by a pulmonologist. The Common Toxicity Criteria for Adverse Events (version 4.03) of the National Cancer Institute 1.4AcquisitionDicom.m”, is responsible for Individually segmentation and extracting organs from CT images. Extracted organs is including the lungs, the heart, Part of body is known as the External and clinical target volume (CTv). Classified information is such that can be display one or more organs in 3D for each patient. A program, “Object3D.m”, is responsible for this task. Data including CT images and spirometry information have only been collected, but other data including organs segmentation, dose-volume histogram (DVH), volume -dose histogram (VDH) and dose-mass histogram (DMH), are processed. A program, ““DVH_Calc.m” and “VDH_Calc.m” based on CT images and dose matrix. For extracting DMH data, in firstly, density based on CT number and then mass of voxels is calculated. A program, “DMH_Calc.m” and a sub program “ToMass.m” are containing above steps. To convert the intensity values of each voxel in the CT images to mass is used transform chart providing by CorePLAN software. In DVH and VDH data extraction is also done by