The performance of the jet trigger for the ATLAS detector at the LHC during the 2011 data taking period is described. During 2011 the LHC provided proton–proton collisions with a centre-of-mass energy of 7 TeV and heavy ion collisions with a 2.76 TeV per nucleon–nucleon collision energy. The ATLAS trigger is a three level system designed to reduce the rate of events from the 40 MHz nominal maximum bunch crossing rate to the approximate 400 Hz which can be written to offline storage. The ATLAS jet trigger is the primary means for the online selection of events containing jets. Events are accepted by the trigger if they contain one or more jets above some transverse energy threshold. During 2011 data taking the jet trigger was fully efficient for jets with transverse energy above 25 GeV for triggers seeded randomly at Level 1. For triggers which require a jet to be identified at each of the three trigger levels, full efficiency is reached for offline jets with transverse energy above 60 GeV. Jets reconstructed in the final trigger level and corresponding to offline jets with transverse energy greater than 60 GeV, are reconstructed with a resolution in transverse energy with respect to offline jets, of better than 4 % in the central region and better than 2.5 % in the forward direction. To reduce the rate of events to be read out from the detector to a rate of around 400 Hz which can be written to offline storage, a rejection factor greater than The large event rate at the LHC makes the online selection of interesting physics events essential for achieving the physics goals of the LHC programme. During the 2011 data taking period, the LHC ran with a bunch spacing of 50 ns providing a nominal rate of 20 MHz, and with a mean of more than 20 separate  trigger  which isThe jet trigger system of the ATLAS detector is the primary means to select events containing jets with high transverse energy  in the detector, containing candidate physical objects which should be examined more closely in subsequent trigger levels. The L1 trigger has a fixed maximum latency of 2.5 The ATLAS trigger , 12, 13 Following the L2 processing, all events with RoIs that satisfy a set of predefined selection criteria are passed to the event builder which reads out the detector at full granularity. These fully built events are then processed by the EF, which also consists of a farm of commodity CPUs. The EF farm runs modified versions of the offline reconstruction algorithms, simplified to improve the speed of execution. Although the full event data are available at the EF, for many trigger signatures the EF trigger reconstruction takes place within RoIs for reasons of speed. This is not the case for the jet trigger, for which the whole detector is read out. The rate of L2 accepted events passed to the EF during 2011 was approximately 3 kHz, and the rate at which events were read out for offline storage was approximately 400 Hz. The ATLAS trigger is illustrated in Fig. In 2011 the full jet trigger was operated in rejection mode for the first time, allowing events to be discarded at each of the three trigger levels. Prior to 2011, the ATLAS trigger selection for events containing jets was based purely on the algorithms running at L1 and L2, with the EF algorithms executed in commissioning mode only. In this mode, events were processed by the EF but not rejected should they have failed the EF requirements. The resulting trigger decision was stored in the event stream for commissioning purposes.FastJet [central or forward, with the central jet triggers using detector data from the central and endcap calorimeters  , is the  maximum , 19.The jet candidate seed the L2 processing in the HLT. The characteristics of jets found using the iterative cone algorithm are tested with a hypothesis algorithm to determine if they fulfil the predetermined L2 trigger selection criteria. These criteria may include minimum values for the jet transverse energy, and selection on the jet pseudorapidity and quality. Each event selected at L2 is then fully built from the various fragments temporarily stored in memory in the data acquisition system.The data from events which pass the L1 selection are processed by the L2 trigger, which has access to the calorimeter cells within the RoIs identified by L1. Limiting the data processed in this way allows the detailed trigger reconstruction of any potentially interesting object, whilst requiring typically only 1–2 % of the full detector data corresponding to the detector elements within the RoIs to be read out. The L2 jet trigger runs a feature extraction algorithm consisting of a simple, iterative cone algorithm , independent of the precision readout used in the HLT and offline. Trigger towers have a size of approximately jet elements, to identify jet candidates and form global Two separate processor systems, working in parallel, run the trigger algorithms. One system, the cluster processor, uses the full L1 trigger granularity information in the central region to look for small localised calorimeter energy clusters typical of electrons, photons or the products of tau lepton decays. The other, used for jet and missing energy triggers, uses coarser granularity In order to handle the large event rate from the detector, following a decision to accept an event at L1, the L2 decision must arrive within approximately 40 ms. Even with the reduction in data volume from reading out only those data corresponding to the RoIs identified by L1, the data preparation at L2 still represents a large contribution to the overall processing time. In this section the data preparation and jet finding stages of the L2 system are discussed.The data preparation for the L2 jet trigger is a crucial part of the L2 processing. It provides the collection of data from detector readout drivers (RODs) , deliverR, such that they contain energy deposits with a separation R, is set during the trigger configuration. The jet energy and position are found through an iterative procedure using the grid in R. Note that the possible directions of the reference jet are discrete due to the 0.2 First, an initial reference jet, k elements from the binned distribution that fall within the , jet finding, and hypothesis testing.full scan. The full scan approach has several advantages for jet reconstruction with respect to the RoI based approach used at L2. The large RoIs required at L2 to ensure that any jet is completely contained has the unfortunate disadvantage that RoIs may overlap in events with high jet multiplicity, resulting in some parts of the detector being processed multiple times. This can result in jets being fully, or partially reconstructed in several RoIs, which may cause the double counting of energy deposits and jets, which would affect the multi-jet signatures. The full scan approach completely eliminates the multiple processing of regions of the detector and, as a consequence, leads to faster processing in high occupancy events, although it takes longer in low occupancy events, where the processing time is in any case low.In contrast to the RoI-based approach used at L2, the EF runs the jet finding algorithm once per event for each configured jet radius, using data from the complete calorimeter. This is referred to as a cell maker and processed to provide the objects upon which the jet finding will then run. Following the jet finding, hypothesis algorithms are executed. These determine whether any specific jet selection signatures are satisfied, for example, typical selections are those based on specific jet Since the output from L2 is in the form of lists of RoIs passing each trigger threshold, a slightly different approach is required to seed the EF processing. In this case, the first jet RoI to be processed by the EF initiates the creation of a dummy, full scan RoI, encompassing the entire detector, required to ensure that the entire calorimeter is processed. The calorimeter cell data for this full detector RoI is then extracted by the The objects from both the data preparation and the jet finding stages are cached for this full scan RoI. When evaluating any additional trigger signature requiring jets passing a different Since the cell data are cached following the data preparation stage, the jet algorithms with different radius parameters run over the cached data and only the jet finding itself will be executed again for each different required radius. In this way the data preparation is common to all jet finding, which is in turn executed only once for each jet radius required. The full sequence for multiple thresholds and multiple jet radius parameters is illustrated in Fig. topological clusters [The jet finder stage can operate with a number of different types of input objects produced by the data preparation from the raw cell data. In early 2011 the primary objects used as input to jet finding were projective calorimeter towers constructed from the raw calorimeter cell information. From May 2011, so-called clusters  were useThe topological clustering algorithm creates clusters of topologically related energy deposits. The algorithm starts with a seed calorimeter cell, with an energy deposit with absolute value greater than four standard deviations above the expected noise. All cells directly neighbouring these seed cells, in all three dimensions, are collected into the cluster. Cells adjacent to the cluster are then added, if they have an energy with an absolute value exceeding the noise by two standard deviations, iterating until all such adjacent cells have been used. Finally, a ring of guard cells is added to complete the cluster. After the initial clusters have been formed, they are analysed to identify local maxima, and split should more than one such maxima be found in a cluster .Jet reconstruction in the trigger is affected by the presence of pile-up interactions, which give rise to energy deposits in the calorimeter that are unrelated to the primary interaction of interest. The overlap of these energy deposits with those of the jets of interest can distort the reconstructed direction and mentclass2pt{minimR, were used in the EF trigger reconstruction in 2011, Jet finding can be performed using any of the available offline jet algorithms. Due to problems with the infrared and collinear safety of cone algorithms , ATLAS hgorithms , 26, andument}kt  algorithument}kt –6, 8. ToLAS cone , 28 jet Should any additional calibrations be required for the final jets themselves, the jet reconstruction process can run a post-processing stage to apply them to jets. As in the case of the offline processing, the EF jet algorithm runs on the full calorimeter information. Differences between the trigger and offline jets generally only arise because the final offline calibrations are not normally available at the time of data taking. During the 2011 data taking the jet trigger was operated at the electromagnetic scale, i.e. with no jet calibration applied.n, the n jets.For an inclusive single jet trigger, the hypothesis algorithm that executes following the jet finding, accepts events which have at least one jet which satisfies the required criteria. Since the jets for each event are cached in memory, subsequent calls to hypothesis algorithms with different selection thresholds simply use this cached jet collection. Identifying multi-jet events is also simply a case of iterating over the reconstructed jets to identify combinations which pass the relevant selections for each signature. Different multi-jet signatures are possible, including those where the chain.The trigger system is configured via a menu which includes the specification of the list of event signatures to be accepted for events written to offline storage. For the jet trigger, this includes the number of jets, j for L2 and the EF, or J for L1. This is preceded by the trigger level separated by an underscore, so for instance EF_j100 would be a 100 GeV single-jet trigger at the EF, and L1_5J10  would be a five jet trigger at L1 with a 10 GeV transverse energy requirement on each jet. Additional items may be included in the name for specialised triggers, such as FJ for forward jets which are required to have a4tc or a10tc indicate that the anti-tc). Where this string is omitted, anti-EFFS to indicate the EF full scan; however, for the following discussion, the EFFS may be omitted from the trigger name for brevity.The names of the trigger selections used in this document consist of the jet multiplicity followed by the pass-through mode, which entails executing the trigger algorithms but accepting the event irrespective of the algorithm decision. This allows the trigger selections and algorithms to be validated, to ensure that they are robust against the varying beam and detector conditions, which are hard to predict before data taking. Partial pass-through mode allows only a certain percentage of events to be passed through the trigger in this way, the rest being subject to the usual trigger selection. This operational mode was used during data taking for several triggers. Passing events through in this way allows data to be collected by the higher threshold triggers for performance evaluation and debugging, with as little bias as possible.Trigger selections at each level are designed to reduce the CPU usage at later trigger levels by maximising event rejection at early stages. Trigger thresholds in the higher levels are tightened to avoid the distortion of the efficiency curve from the slower-rising efficiency of previous levels. Triggers can operate in bunch groups, which allow triggers to include specific requirements on the LHC bunches colliding in ATLAS. Not all bunch crossings contain protons; those that do are called filled bunches. For the random trigger, filled bunch crossings were required, indicated in the trigger name by FILLED at L1, and filled at L2. Non-collision triggers require a coincidence with an empty or unpaired bunch crossing, which correspond respectively to no protons in either LHC beam or a filled bunch in only one beam. For some of the lowest threshold physics triggers, a corresponding non-collision trigger was included in the chain for background studies.Further flexibility is provided by defining As well as the trigger chains selecting jets at both L1 and L2, there were chains running at the EF, which were seeded by a random trigger at L1, and passed the events through L2 without running a selection algorithm. These allowed triggering on very low Event Filter triggers that reconstruct a10);jet triggers where the jet algorithm is executed with a large-TE, differing with respect to the heavy ion triggers, used for the Pb+Pb data taking period at the end of 2011, having a total transverse energy requirement in GeV denoted by The first time ATLAS used both the L2 and EF stages of the HLT in event rejection mode was in 2011. A number of key improvements were introduced during that year, including the ability to use topological clusters rather than calorimeter towers at the EF, as discussed in Sect. In addition to the more common jet triggers such as inclusive single jet, and multi-jet triggers, some specialised jet triggers, dedicated to more specific physics signatures, were used in 2011:prescale factors are used to suppress the rates from signatures with lower thresholds. A prescaled trigger selects only a fraction, 1/prescale, of events that would otherwise pass the trigger. For the best expected statistical significance, wherever possible, triggers intended for searches or analyses requiring the highest possible number of data events, should not be prescaled. As the luminosity increased during 2011 data taking, the prescale factors applied to the triggers with lower thresholds were increased accordingly, to ensure that the output rate remained within the available bandwidth for writing to offline storage. Figure In order to keep the rate from the jet trigger within the allowed bandwidth, In addition to applying prescale factors to low-threshold triggers, the EF entclass1pt{minimaAs a hardware system, the L1 trigger operates with a fixed latency, whereas the L2 and EF systems operate with a variable processing time, and must complete their respective processing within the constraints provided by the L1 rate, the rate at which events can be recorded offline, and the number of available CPU nodes in each HLT farm. In this section, the time taken to process events for the L1 system and the HLT is discussed.The L1 jet trigger is a fixed latency, hardware based trigger operating synchronously with the LHC bunch clock and the rest of the L1 system. The pipelines in the detector front-end electronics are typically 120 bunch crossings deep and as such the latency from the complete L1 processing must fit within the corresponding time. Throughout the L1 system each step is handled in parallel with other steps. Data transfers between parts of the system are performed concurrently with the processing of the data that has already been transferred. The analogue data are digitised and sent as input to a jet algorithm, and the final decision is sent from the L1 calorimeter system to the central trigger processor (CTP). The jet algorithm processing itself is very fast and takes only approximately 50 ns, but represents only part of the processing necessary to reconstruct jet candidates, the rest being in formatting the input and output data such that the algorithm can execute quickly. The overall time for all these stages including the transmission of the results of the calorimeter trigger reconstruction to the CTP is approximately 1.5 In this section, timing distributions are presented for a physics run taken during October 2011. During this run, the peak instantaneous luminosity was 3.5The execution time of the algorithm per event, rather than per RoI shows a clear peak around 6 ms and a second peak around 12 ms, due to events containing two RoIs. The data preparation time for the full event has a peak at around 3 ms for single RoI events and another from the two-RoI events around 6 ms. The algorithm CPU time has corresponding peaks around 4 and 8 ms.At the EF, following the data preparation steps – the retrieval of calorimeter cell information from memory and building of topological clusters – a single instance of the anti-After the jet finding has completed, the selection hypothesis algorithms are executed both at L2 and the EF. For the single inclusive and multi-jet triggers the hypothesis algorithm typically executes in approximately 10 An important concern for the trigger reconstruction is the producion of objects resembling as closely as possible those later reconstructed offline, to allow informed event selection with high efficiency while minimising any increase in the trigger rate. This is achieved by reducing any finite trigger–offline resolution or bias so that any selection of objects on the basis of trigger quantities more closely corresponds to the offline selection used for physics analyses. For this reason, the performance of the jet trigger during 2011 data taking has been evaluated with respect to the offline jet reconstruction. The offline reference jets have been reconstructed using the infrared and collinear safe anti-lgorithm  implemenlgorithm  package.The trigger performance is defined in terms of specific metrics, comparing offline and trigger reconstructed jets, such as jet selection efficiency, and the transverse energy or angular resolution with respect to offline jets. Comparisons of the same metrics with Monte Carlo simulated samples are shown in this and the following sections to illustrate how well the simulation describes the data and where disagreements appear. It should be emphasised, however, that the focus is on performance indicators determined from collision data, and detailed comparisons of different simulation configurations are beyond the scope of this paper.It is informative to evaluate the performance of the trigger in simulated events and compare it to the real trigger running in collision data. The ATLAS trigger simulation runs exactly the same code for the HLT as that run online, and a very precise emulation for L1. The differences observed between collision data and simulation are due either to differences in the underlying physics, such as the composition and internal topology of the jets themselves, or to the kinematics, hadronisation, treatment of underlying event, or to differences in the simulation of the detector response or the detector conditions.Because of these potential sources of differences between data and simulation, for jet physics analyses, trigger selection and trigger related calibrations are generally obtained using the data rather than relying on the trigger performance from the Monte Carlo simulation. Therefore, while it is desirable for the simulation to accurately reproduce the behaviour of the trigger, it is by no means essential.For the evaluation of the trigger performance, events are selected from those written offline that are free from known problems with the detector or beam conditions. From these events, offline reconstructed jets which satisfy standard ATLAS jet selection criteria used in physics analyses –6 are sepass through events, where the trigger accepted the event irrespective of the trigger jet selection, as discussed in Sect. The efficiency for each specific chain has been evaluated using events selected by an alternative chain which is unbiased by the selection of the chain being evaluated. Therefore, wherever possible, the efficiencies have been evaluated using trigger chains seeded by a random trigger at L1, passing through L2 and EF without additional trigger selection. Where this was not possible, the standard chains have been used, but selecting only those Herwig [Pythia [Herwig, the formation of hadrons from the final state quarks and gluons produced in the parton shower is described using a cluster hadronisation model [Pythia generator uses the Lund string fragmentation model [There are a number of general purpose event generators for LHC physics: for more complete review, see elsewhere . In the Herwig  or Pythi [Pythia  Monte Caon model , whereason model , 37.In the following discussion the central and the forward jets triggers are discussed separately. For central jet triggers in the range For offline analyses, jets are corrected for the difference between electromagnetic and hadronic responses in the calorimeter. Therefore jets can be defined either at the electromagnetic (EM) scale, which correctly measures the energy deposited by electromagnetic showers in the calorimeter, or after the full hadronic jet energy scale (JES) calibration , 38. In Descriptions of the metrics used to assess the jet trigger performance can be found in this section: specifically for the efficiency measurement, and the evaluation of the resolution and bias arising from any offset between the trigger and offline reconstructed quantities.per jet efficiencies with respect to the corresponding jet reconstructed offline. This represents the probability that an offline jet will have a corresponding jet reconstructed in the trigger that satisfies the trigger selection. Efficiencies per event can also be defined, in terms of global event properties, such as the per event selections may be very informative; this is discussed further in Sect. Unless otherwise stated, the inclusive single jet efficiencies presented in this paper are of the form of N, passing some selection which defines the sample, and the number of those jets, m, which are also reconstructed in the trigger to within some appropriate matching criteria, such that The jet reconstruction efficiency, vice versa. This is important since the correspondence of offline jets to trigger jets is not one-to-one.The choice of matching criteria must be considered as an important aspect of the definition of the efficiency, since a tighter matching will necessarily result in a lower efficiency and The binned differential efficiency, Figure For the matching used to define the resolution and efficiency, criteria in The trigger system selects jets based largely on the efficiency plateau region, where the efficiency is above 99 %.A more slowly rising edge is expected at L1 due to the poorer The transverse energy resolutions and offsets are computed from the distributions of the residuals between the quantities computed offline and at trigger level.To provide a single statistic to parameterise the resolution, the root-mean-square (RMS) deviation of the central 95 % of the residual distribution is used. This is further divided by the RMS for the central 95 % of a Gaussian distribution with unit standard deviation. In this way, if the distribution were Gaussian, the normal Gaussian resolution would be obtained. This measure was chosen because the RMS of the full distribution can be strongly biased by significant non-Gaussian tails. Similarly, a measure for the resolution based on the width of a Gaussian distribution fitted over the central region of the distribution will fail to take into account a significant fraction of the distribution if there are large tails and will not be representative of the actual performance.Offsets and resolutions between jets reconstructed in the trigger and reconstructed offline are obtained from the distribution of the quantityUnderstanding of the offsets and resolutions in the data is useful for the determination of the behaviour of the trigger efficiencies near the As the resolutions and offsets presented in this section are with respect to offline jets at the EM+JES scale, large offsets are expected. For brevity, only the performance of the EF trigger is presented as this corresponds most closely to the offline reconstruction. Since physics analyses generally use In order to ensure that the trigger has reached plateau efficiency for the lowest L1 jet Herwig simulated sample integrated over Figure A large The relative offset in the data is in general slightly more negative than that shown by the Monte Carlo simulation. The size of the offset of the EF trigger jets with respect to offline jets tends to decrease for the higher In Fig. As a result, the mean offset and resolution in Because of the large dependence of the offset on Figure Figure The offsets and resolutions with respect to offline jets as a function of offline mentclasspt{minimaAll of the above results compare electromagnetic-scale jets, as measured by the trigger, with offline reconstructed jets at the EM+JES scale. In this section, trigger jets are compared to offline jets reconstructed at the EM scale only, to better illustrate the correspondence between the reconstruction in the trigger and offline when the same calibrations are applied to both.Figure The resolutions as a function of the offline jet pseudorapidity and The difference in the offsets observed between the EM and EM+JES jets serves to illustrate the size of the correction applied during the JES calibration and suggests that, should the same correction be applied online, the correspondence between offline and trigger reconstructed jets would be better than a few percent with resolutions of better than 3 %. Since 2012 the JES calibration has been applied to the trigger jets online.To understand the performance of the trigger in more detail, the trigger efficiency versus Measuring the efficiency in data requires events to be selected with an independent reference trigger which is unbiased with respect to the trigger being studied. The reference trigger is usually chosen to have a lower The efficiency curves for a selection of single inclusive jet triggers as a function of Herwig sample would have a correspondingly higher In Sect. The efficiencies as a function of forward region, defined as having a pseudorapidity Figure The offset and resolution of the trigger, and the underlying kinematics, each affect the rising edge of the trigger efficiency as it increases towards plateau.The resolution and offset of the trigger jets have been shown to vary significantly with pseudorapidity. This has a significant effect on the trigger efficiency and introduces a strong dependence on the pseudorapidity, of both the position of the midpoint and the sharpness of the rising edge of the trigger, and of the To quantify the behaviour of the trigger efficiency in the vicinity of the rising edge as a function of pseudorapidity, it is informative to study the efficiency, differential in N jets in the event pass certain A multi-jet trigger requires that However, the principal disadvantage of a multi-jet trigger is an overall loss in efficiency due to limitations in both transverse energy and angular resolution at L1 and L2. This loss in efficiency is compounded by the jet multiplicity requirement in the trigger, but is less significant for offline jets when they are geometrically isolated. The primary reasons for these inefficiencies in the trigger are the use of the square sliding window and reduced granularity at L1, and the limited RoI size used for the reconstruction of jets at L2.Multi-jet triggers have been used in signal selection and multi-jet background estimation in searches for the Higgs boson, supersymmetry, and other, beyond-the-SM, processes –41. DuriN jets with a single common threshold, the efficiency will essentially be determined by the efficiency for triggering on the N-th leading jet in event level efficiency, determined as a function of the N-th jet.For a multi-jet trigger efficiency, when requiring a signature containing The characteristics of multi-jet triggers are illustrated in Fig. midpoint of the rising edge, in GeV, sharpness of the rising edge, and In order to allow a very approximate quantitative comparison of the efficiency for a selection of jet triggers with different multiplicities, a fit to the efficiency distributions for four multi-jet trigger chains has been performed and the relevant parameters extracted. A sigmoid function was chosen to parameterise the efficiency,The plateau efficiency was also determined using the parameters from the sigmoid fit and, additionally, fitting a constant to the region Table The plateau efficiency decreases with increasing jet multiplicity because of the limitations of accurately reconstructing jets which are not well separated and discriminating between them at L1 and L2.Figure pp data, jet triggers designed to reconstruct specific physics signatures are used in the ATLAS trigger. In 2011 these included To further exploit the In many searches for physics beyond-the-standard model (BSM), including Supersymmetry (SUSY) and other exotic physics signatures, the hard process gives rise to a final state containing energetic jets and a large missing transverse momentum. The selection adopted to discriminate the signal process from the background in such searches typically includes requirements on the triggers  can be uThe  leptons . Single,To illustrate the The quantity The efficiency with respect to the offline Figure In conclusion the performance of the Physics analyses studying the properties of, or searching for, new or heavy particles decaying into boosted hadronic final states, may include kinematic regions where the decay products are more collinear. Such events may not be triggered by standard  collisions differ significantly from  studies –50. Studllisions .The study of a full range of observables which characterise the hot and dense medium formed in HI collisions is possible with specific HI triggers. In addition to global measurements of quantities such as particle multiplicity and collective flow, electroweak gauge boson production, heavy-quarkonia suppression, and the modification of jets passing through the dense medium are accessible with ATLAS data –50.centrality of the collision, defined as the The dominant issue for jet measurements in the HI environment is the presence of a large amount of additional energy coming from the underlying event (UE), additional interactions originating from the same Pb+Pb collision. The properties of this energy depend on the impact parameter, or minimum transverse distance between the two colliding nuclei. A direct measurement of the impact parameter is not possible and so the e the UE . The disThe 0–10 % centrality bin represents the most central collisions, with the smallest impact parameter and the largest UE contributions. The 60–80 % centrality bin represents the most peripheral collisions used in this study, corresponding to the largest impact parameters and the smallest UE contributions. Jet reconstruction in HI events typically corrects for the contributions of the underlying event.During the first LHC Pb+Pb run, in 2010, all events identified by the minimum bias (MB) and forward detector triggers , 13 wereThe L1 MB triggers based on the total summed transverse energy in the calorimeter were used as the L1 seeds for HLT triggers which reconstruct high lsewhere .i). The background subtracted cell energies  using the anti-The performance of the HI jet trigger is evaluated here using the Pb+Pb collision data recorded near the end of the 2011 data taking period which corresponds to an integrated luminosity of 140 Pythia [Hijing [Offline jets are reconstructed from calorimeter towers, using the anti-g Pythia  embedded [Hijing  event getimation . Figure lsewhere .Fig. 26Ttrack jet - a jet formed using tracks from charged particles rather than calorimeter energy deposits. In this case, track jets are reconstructed using the anti-In HI events it is not uncommon for fluctuations in the UE to create regions with high The efficiency of a trigger is defined as the per jet probability to satisfy the trigger requirements as a function of offline jet The performance of the jet reconstruction by the trigger over a range of centralities and radius parameters typically used in HI analyses is illustrated in Fig. Figure The angular resolution of trigger jets with respect to offline jets with pp physics. A small efficiency degradation with increasing centrality is observed, which is less pronounced for smaller radius parameters. The angular resolution is good, but shows some centrality dependence for larger radius parameters.The heavy ion programme at the LHC will provide crucial information about the formation of a hot evanescent medium at the highest temperatures and densities ever created in the laboratory. The ATLAS jet trigger algorithm performs well in the HI environment, using the same anti-The ATLAS jet trigger has been designed to provide an online reconstruction of jets matching as closely as possible those from the offline reconstruction. For this reason, while the RoI approach is mandatory for reasons of bandwidth limitation at L1 and L2, during Run 1 the jet trigger for the EF processed events using the full calorimeter data and using the same anti-The time required for the complete processing of the full ATLAS jet trigger menu per event in the HLT during 2011 had a mean of below 300 ms, well within the required budget for HLT processing.For the L1 jet trigger, the lowest threshold deployed during 2011 data taking was 10 GeV at the electromagnetic scale. This trigger was fully efficient for offline jets above 45 GeV. The lowest threshold HLT chain which included a L1 jet seed, selected jets reconstructed in the HLT with transverse energy greater than 25 and 30 GeV at L2 and the EF, respectively. These triggers were fully efficient for offline jets above approximately 60 GeV.For unbiased trigger selection of jets with lower For offline jets with More specialised triggers, intended specifically for searches for signatures of new physics, or for measuring the hadronic decay products of highly boosted massive objects, were operational in 2011 and are seen to perform well. The jet trigger for heavy ion physics was also seen to perform well, benefiting significantly from the full scan approach of the Event Filter to reduce the processing time that would have been required by a purely RoI based approach in such a high occupancy environment.


Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the The online version of this article (doi:10.1007/s10822-017-0074-x) contains supplementary material, which is available to authorized users. The binding of a small molecule (ligand) to a macromolecule  is a key process in biology and the most common mechanism for pharmaceutical drugs to act. A long-term goal of computational chemistry has been to accurately predict the binding free energy of a given protein–ligand pair. Several rigorous methods have been developed, which in principle are only limited by the accuracy of the underlying energy model (force field). These methods are typically based on molecular dynamics (MD) and include potential-of-mean-force methods, in which the ligand is physically dragged in or out of the binding cavity, as well as alchemical perturbation methods, in which an unphysical path is applied.binding pose, to converge in a reasonable time [molecular docking (or simply docking), typically involves a combination of a conformational search method and a scoring function that approximates the binding affinity for a given candidate. The receptor is usually considered rigid and the ligand flexible. However, some methods take the flexibility of the side chains in the receptor into account [In practice, most of these methods require the knowledge of the structure of the protein–ligand complex, the ble time . Thus, p account –4, for e account , 6, or s account .reconnaissance metadynamics, which uses a machine-learning approach to apply a local bias potential that helps escaping the free-energy basins in the conformational space [Given the limitations of both conformational search methods and scoring functions, there is a growing interest in more rigorous approaches to the binding pose prediction problem. The direct use of MD simulations to find the binding pose has been tested for several systems –10. In pal space . In a pral space . Methodsal space .A more common application of MD simulations is to validate a binding pose obtained by docking . The purDrug Design Data Resource (D3R) Grand Challenge was conducted in 2015, with a first stage dedicated to pose prediction and ability to rank compounds by binding affinity with minimal structural data, and a second stage dedicated to ranking compounds when at least a subset of the binding poses were known. A conclusion from the challenge was that the accuracy of pose-prediction methods depends on several extrinsic factors, such as which protein structure was used for the docking, how protein structures were prepared, and other aspects of the protocol [D3R Grand Challenge 2, was initiated in 2016. In the first stage of this challenge, the goal was to determine the binding pose for 36 different ligands to the farnesoid X receptor (FXR) with computational methods. FXR is a ligand-activated transcription factor, attributed to many bodily functions, e.g. regulation and maintenance of bile acid synthesis, reduction of plasma cholesterol and triglycerides, glucose homeostasis and improvement of insulin sensitivity [To assess the isolated pose-prediction problem, a crystal structure of the complex is needed, but then, on the other hand, there is a risk that studies get influenced by this knowledge. Therefore, blind challenges, in which there exists accurate experimental data for validation but the data is kept secret during the prediction phase, play a very important role. The first protocol . A seconsitivity .mis-docked poses in a reasonable amount of simulation time. Therefore we also include a third round of calculations, in which we apply an enhanced-sampling approach, namely reconnaissance metadynamics, to explore the generation of diverse binding pose candidates.The aim of our participation in the D3R Grand Challenge 2 is to investigate whether rigid docking into a multitude of crystal structures, followed by extensive MD simulations, can solve some of the problems for which one would otherwise expect more advanced flexible docking methods to be required. In particular, we anticipate that the simulations, with their more accurate treatment of e.g. water, can refine resonable docking poses and bring them closer to the experimental structure. In light of previous research, we do not expect the MD simulations to be able to repair challenge in the following) involved predicting the binding pose of 36 ligands binding to FXR. One of the ligands (33) was subsequently discarded from the data set due to experimental problems; thus it will not be included in this manuscript.The pose prediction part of the D3R Grand Challenge 2  to analyze the results or guide the selection of computations to perform. However, because the aim of the study was to develop “blind” methods, we will clearly mention when and why the secret data was used.The preparation and parametrization of the ligands were done in a blind manner (i.e. without using secret data) and kept constant throughout the study. First, hydrogen atoms were added at pH 7.4 to the 2-dimensional molecular structures using Open Babel  followedAn apo conformation of FXR was given at the start of the challenge, and was used as a template for the submission of binding poses. To account for the known conformational variation in the protein, a set of 18 ligand-bound crystal structures of FXR from the Protein Data Bank were prepared alongside the apo-protein .For each crystal structure, chain A was isolated by removing all water molecules as well as any redundant protein chains. To eliminate the dependence of the results on particular crystallographically motivated mutations in the various structures, all protein structures were modified by point mutations using the ’swapaa’ command in UCSF Chimera  until thThe apo structure was analyzed with the web server H++ , which pa posteriori analysis, a similar procedure was used to prepare the new (secret) crystal structures for simulations, as detailed in Table S3 in the Supplementary material [For the material , 36. OwiMolecular docking was performed by Autodock Vina, which is an open source docking programme widely used by many research groups for docking and virtual screening studies. It employs an empirical scoring function  which isAutodock Vina uses a fixed grid box wherein it tries to place the different conformations of the ligand. In our case, the previously published crystal structures of FXR–ligand complexes indicated a single well-defined binding site. The AutoDock Tools  were useThe docking was performed with the “exhaustiveness” set to 8. Increasing the exhaustiveness would increase the probability of finding the global minimum, but we preferred to set it to a typically used value. As the docking procedure involves random seeds, different results are obtained in every run; we simply used the first set of results that we obtained.Each ligand was docked with every crystal structure, including the apo-protein, in total 35 × 19 docking runs. After the secret data was revealed, we extended the docking study to include the new crystal structures. Again, each ligand was docked into all available crystal structures and all parameters of the docking protocol were kept identical.ff14SB force field [For each ligand, the top-predicted docking pose, i.e. the prediction with the best score among all included crystal structures, was used as the starting point for an MD simulation. The Amber ce field  was usedAll simulations were run with GROMACS 4.6.2 . The acpA 1 ns NPT equilibration , with positional restraints on the ummation  using a ummation .The production MD simulation was performed with the same settings as the previous equilibration, but without any restraints. In order to check the stability of the binding pose, an RMSD calculation was performed after each ns of MD simulation to see whether the ligand position deviated too much from the starting position. If the RMSD of the ligand  than ordinary metadynamics and related methods [Reconnaissance metadynamics (RMD) simulations were performed for all the complexes subjected to MD simulations, using the end points of the MD simulations as starting points for the RMD simulations. RMD is a self learning algorithm for enhanced sampling which is capable of handling a larger number of  methods . The RMD methods  patched The complete set of rotable bonds in each ligand was determined manually and the corresponding dihedrals were used as CVs in the RMD algorithm. The RMD simulations were performed with the same settings as the previous MD simulations except that they were performed in the NVT ensemble  to avoid technical issues. The bias deposit stride was set to 1 ps with a gaussian width of 1.5  and a gaussian height of 0.239 kcal/mol. The basin tolerance was set to 0.2 the basin expand parameter to 0.3 and the basin initial size to 1.5. The RMD clustering stride was 100 ps, with 1000 data points collected during this period. RMD simulations were run for 20 ns and the results were interpreted by a clustering approach, as described below.For some ligands, we also ran an RMD simulation with the ligand dihedrals and seven additional CVs intended to increase the fluctuation of the protein sidechains in the active site. These were the dihedral angle around the For ligand 5, we also ran an RMD simulation with the ligand dihedrals and three additional CVs intended to promote rotation of the ligand with respect to the protein. These were again dihedral angles, but each connecting two maximum common substructure procedure [Two types of RMSD analysis were performed in this study. To analyze the difference between various poses, perform clustering, and analyze the stability of a simulation, the standard GROMACS tools were used, with the RMSD calculated for the heavy atoms of the ligand after alignment of the rocedure  to matchGROMOS algorithm [Cluster analysis was performed with the GROMACS tool g_cluster using the lgorithm  with theFor preparing the docking submission to the challenge, all poses for a given ligand were ranked according to their score, and any duplicate poses were removed by going through the sorted list of poses and discarding a pose if a similar pose with better score had already been selected, possibly based on another crystal structure. The criterion for similarity was that the RMSD between the poses was below 2 Å. The top five poses for each ligand were submitted in the challenge, ranked according to their score.For preparing the MD submission to the challenge, the clusters of the MD trajectory were ranked according to size (i.e. the number of snapshots). The center of the largest cluster was used as the top pose. In most cases, only one significant cluster was obtained, and in the few cases in which several (up to four) significant clusters were obtained, the extra clusters were found to be uninteresting and will not be further discussed.When preparing the RMD submission to the challenge, only three ligands were ready. The poses for these ligands were selected by manually combining data from RMD and additional MD simulations, as described in Table S2 in the Supplementary material. For all other ligands, the MD submission was reused.For computationally predicting binding poses to FXR, we investigated the performance of a rigid but multi-targeted docking method and further refinement by MD and enhanced sampling, all in a blind-challenge context provided by the D3R Grand challenge 2. Our long-term goal is to develop a useful combination of these methods which can be applied to protein–ligand complexes with unknown structure. The results will be presented and analyzed step-wise, beginning with docking results, continuing with results from MD simulations, and ending with the results from reconnaissance metadynamics.To account for the known flexibility of FXR and increase the probability of finding the correct binding pose despite using a rigid docking method, each ligand was docked into a series of crystal structures from the Protein data bank, as described in the method section. In the analysis stage, this set of protein structures was further extended by the 35 new crystal structures and a similar docking procedure was performed.0lxp5) consisted of five predicted poses for each ligand, ranked according to their score. The evaluation results (RMSD towards experiment) are shown in Table find the binding pose, whereas the “first” measure also tests the ability to rank the poses.Our docking submission , although for the remaining eight cases the difference in score was always smaller than 1 kcal/mol  or from having the sidechains in exactly the correct conformation for optimal interaction. From the data in Table The “globally best” column in Table To analyze the performance of the scoring function, we posed the question of whether our multi-targeted docking approach would have picked out the correct pose if the challenge had included the secret crystal structures of the proteins (but no information about binding poses or which protein structure corresponded to the particular ligand). More precisely, we extracted the RMSD towards experiment for the single pose having the best score among all the dockings to old and new crystal structures. The results are given in Table With this larger set of data, it is interesting to know whether the difference in docking score between the correct pose and the top-predicted but wrong pose is always small, as was indicated by the data for the old crystal structures (see above). We thus defined the correct pose as the globally best-scored pose with an RMSD below 2 Å, and excluded ligands for which no such pose was found. The detailed results are shown in Table S5 in the Supplementary material. Out of the 10 ligands for which the top-predicted pose was wrong, 5 displayed a score difference smaller than 0.5 kcal/mol, which can be considered well within the accuracy limit of the scoring function; one should probably consider all poses equally likely if their scores differ by such small amount. On the other hand, for the remaining 5 ligands, the difference was greater than 1 kcal/mol and in one case, for ligand 18, as high as 3.4 kcal/mol. This suggests that these interactions are quite complex and not well modeled by the scoring function. However, part of the reason for the failure of the scoring function might be that the “correct” poses were not perfect; only one of the 5 ligands with large score difference had an RMSD below 1 Å towards experiment. In particular, the best found docking pose of ligand 18 (RMSD 1.2 Å) had one amide group oriented in the wrong direction, thus preventing the formation of a hydrogen bond with His-451; this can probably explain the rather poor score and the resulting prediction of an unrelated pose (RMSD 8.8 Å) as the best one .7ltme and ixnzu) have been included in Table For comparison, the results for the two best submissions in the challenge (byf51) in the challenge, but with no improvement relative to the docking results. Later, the set of MD simulations was extended to include all docking poses that were within 3 Å of the experimental structure, regardless of their initial rank. This enabled us to collect more statistics on the possible use of MD for refinement of reasonably correct poses, as we did not expect MD to repair the mis-docked ones. In total, 48 simulations starting from docking poses were run (but the one for ligand 33 was discarded). For comparison, a series of simulations starting from the experimentally obtained binding pose for each ligand were also performed .A subset of the docking poses were selected for refinement using classical MD simulations, followed by clustering, as described in the method section. Originally, this subset included the top-predicted pose of each ligand; the cluster centers of these simulations were submitted as a separate entry  in the MD refinement, reflecting an almost equal probability of improvement (60%) and deterioration (40%). The individual variation is shown in Fig. The results for the simulations that were started from the experimental structures are also given in Table The reason for the experiment-based simulation poses deviating from the experiment for some ligands is probably the limited accuracy of the force field, which is caused by the use of generic torsional parameters as well as the intentionally “blind” preparation of partial charges for each ligand .On the other hand, the reason for most simulations staying close to the starting structure despite force field deficiencies is most likely the relatively short simulation times, which did not allow for larger rotation of the ligand in the binding site. Indeed, both the docking-based and experiment-based simulations showed a similar distribution of the RMSD during the simulations see Fig. , and a sMM-PBSA analysis of MD trajectories in the Supplementary material. In summary, the method correctly predicted the experimental pose to have the most negative binding free energy for all six tested ligands  and thus seems to be useful for this particular purpose. However, especially for the charged ligands, it was difficult to estimate the systematic error in applying the method to different poses, and thus further investigation would be needed to establish the significance of the results [Finally, we tested whether the MD trajectories could instead be used in a MM-PBSA context to help ranking the binding poses. More specifically, we selected six example ligands, for which the Autodock Vina scoring function mis-ranked the poses. For these ligands, we investigated whether MM-PBSA provided sufficient precision to discriminate between various binding poses and, in such case, whether it ranked the poses in agreement with their RMSD towards experiment. The details of this investigation, including a thorough discussion of the results, are given in the section  results .To investigate whether reconnaissance metadynamics (RMD) can be used to enhance the sampling and thereby explore new binding poses, we performed RMD simulations using the dihedral angles of the rotable bonds in each ligand as collective variables (CVs). During the blind challenge, only three systems  were subjected to RMD simulations due to the limited time, and no improvement was obtained for these . Later, we extended the RMD investigation to include all the MD-simulated systems  to obtain better statistics.The results of the RMD simulations are summarized in Table On average, a minor improvement in the RMSD towards experiments was obtained (by 0.6 Å). More importantly, the RMSD of the “farthest” RMD cluster was significantly higher than that of the MD cluster for all ligands . From the overall distribution of the RMSD shown in Fig. For three ligands , we performed additional RMD simulations with an extended set of CVs including seven dihedral angles of protein sidechains that were identified by visual inspection as possibly restricting the ligand movement. The purpose of these simulations was to see whether the exploration of new poses would be stimulated if the enhanced sampling of the ligand dihedrals was accompanied by enhanced sampling of these selected sidechain dihedrals. For example, one could imagine that a certain rotation of the ligand could, due to steric hindrance, only take place when a certain sidechain adopts a particular conformation. Covariance between the two types of fluctuations could then in principle be detected by the RMD algorithm, with the applied bias increasing the probability of the two movements to occur simultaneously.Interestingly, the introduction of sidechain CVs actually decreased the fluctuation of the ligand . The reason for this counterintuitive behavior is probably that RMD is designed to find the path with the lowest energy barrier out of a given basin. If the sidechain CVs are “softer” degrees of freedom with lower energy barriers between the local minima than the ligand dihedrals, the algorithm will seek the “easy way out” and predominantly enhance the fluctuations of the sidechain CVs, thus exploring the conformational space of the ligand at a lower pace than without the sidechain CVs. Indeed, the obtained poses were less varied in the simulation with sidechain CVs, as demonstrated in Fig. S6, S7 in the Supplementary material.Finally, for one ligand (5), we tested to include three CVs related to the orientation of the ligand relative to the protein , in addition to the ligand dihedral CVs (but no sidechain CVs). The purpose of the orientational CVs was to enhance the rotational movement of the ligand, thereby counteracting the steric restrictions imposed by the surrounding amino acids. The results show that the ligand rotated much more when these CVs were included . Moreover, the RMSD towards the starting structure grew faster and the number of explored poses increased, as illustrated in Fig. Ligand 11 was selected for a more detailed investigation because it diverged more than 2 Å during the MD simulation starting from the experimental crystal structure. The best cluster of the RMD simulation had slightly smaller RMSD (1.9 Å), so it is interesting to investigate not only how the simulated poses differed from the experimental pose in terms of interactions, but also what caused the slight improvement in the RMD pose. From a visual inspection see Fig. b, it is A protein–ligand interaction analysis for these three complexes further highlighted these differences. In the experimental structure, the tetrazole ring of the ligand formed two hydrogen bond interactions with Gln-267 and Arg-268, respectively  and reconnaissance metadynamics (RMD) when used as pose-prediction methods for this particular system.The procedure to use multiple protein structures for docking to account for the known conformational variation worked very well in this case, allowing us to find correct binding poses for 21 of the 35 ligands and placing our docking submission in the upper half of the submissions to the D3R Grand challenge 2. However, for 8 of these successful ligands, the correct pose was not predicted as the top pose, which suggests room for improvement in the scoring function used in Autodock Vina. Inclusion of the new (secret) protein structures in the docking set would have increased the number of correct poses to 29, but still 6 ligands would have remained mis-docked, most of them classified as miscellaneous. This confirms the data set as rather difficult.The MD refinement of the docking poses did not provide any significant improvement; in fact the RMSD towards experiment increased in almost half of the cases. The simulations showed a remarkable kinetic stability for almost all of the docking poses, regardless whether they were correct or not. Thus, stability in MD simulations of length The subsequent RMD simulations were successful in exploring new binding poses, but never visited the experimental structure if started from a mis-docked pose. One of the problems seems to be that by only applying bias potentials on the internal dihedrals of the ligand, one does not promote rotation of the ligand with respect to the protein. Another problem is that the tight environment around the binding site sterically restricts the ligand’s exploration of conformational states. Preliminary tests were made to include collective variables that tackle each of these problems, but further development is needed to accomplish this task. In the future, we believe that such carefully devised collective variables may contribute towards a reliable method for improving docking poses by simulations. An important problem that remains, however, is how to reliably identify the most stable pose from trajectories of a limited length.Supplementary material 1 (PDF 11526 kb)Below is the link to the electronic supplementary material.


The clinical effectiveness of percutaneous and transforaminal endoscopic discectomy procedures has been evaluated by the system used or compared to open laminectomy or micro-discectomy but are not evaluated based on the location and characteristics of the abnormal disc. This review proposes that outcomes are primarily related to disc size, biomechanics, location, and associated segmental fibrotic and bone changes as well as the surgeon's skill in using various systems rather than the specific system used. In these cases, the surgeon needs to decide if the goal of the procedure is simply internal decompression of an abnormal but contained herniated disc or release of the entrapped nerve root by a large contained disc, extruded and migrated disc fragment, or coexistent foraminal stenosis. Percutaneous and tubular transforaminal procedures are quite different, technically ranging from simple discectomy aspirating probes to larger endoscopic systems, providing the capability to remove large extruded free disc fragments, with or without foraminotomy. Recently, the ability to perform interbody fusion has been added to the range of procedures able to be performed endoscopically. At the same time, biologic solutions to disc degeneration are rapidly evolving and may have a place in combination with these procedures. This article reviews the interrelationship between clinical signs and symptoms, radiologic findings, and the biochemistry and biomechanics of the affected disc segment. Understanding the role played by all these factors enables the surgeon to evaluate both the disc and surrounding bone structures pre-operatively to determine if the clinical signs and symptoms are related to enlargement and displacement of a contained disc or compression or impingement of the nerve root. Based on this, the surgeon can choose different surgical systems, allowing simple decompression of a contained disc, possibly adding biologics, with a 'small' system, while a large herniated disc, or extruded fragment, causing root impingement, would require a ‘larger’ system that provides direct endoscopic visualization within the epidural space, foraminal decompression with drills, and direct surgical manipulation and freeing of the nerve root. By choosing the surgical system based on characteristics such as disc size, location, and associated inflammatory and fibrotic changes, the effectiveness of minimally invasive procedures will be more consistent and improve as the surgeon's diagnostic and operative skills improve. The literature regarding percutaneous and transforaminal endoscopic discectomy has focused on the effectiveness of specific systems rather than how the actual procedure performed relates to the underlying disc pathology . Disc paThe key to selecting the proper surgical procedure for symptomatic lumbar spine abnormalities has always been accurate diagnosis and understanding of the capabilities and limits of any given surgical technique in combination with the skill of the surgeon. This applies whether it is open surgery or minimally invasive and endoscopic procedures. The role of spinal biomechanics is also critical since understanding the cause of symptoms, and the effect of the surgery on spinal motion, and abnormal physiology and motion of the disc and spinal segment helps to determine the best surgical approach to the abnormal disc as well as the area causing nerve root compression. The major advantage of all minimal spinal lumbar procedures is to access and remove abnormal pathology while preserving the anatomy and function of the muscles, ligaments, and bone structures, thus providing faster patient recovery, better lumbar support, and preserving as much normal spinal motion as possible. As minimally invasive tubular and endoscopic procedures have technically advanced and become commonplace, it is also critical to understand the limits of each procedure and the fact that all preoperative decisions and surgical planning is based on detailed computerized tomography (CT) and magnetic resonance imaging (MRI) and relating these radiologic findings to the patients' signs and symptoms . The surRadiologic evaluation of the lumbar spine and discThere are numerous classifications and grading systems based on CT and MRI scans to ‘quantify’ the severity of disc changes and degeneration. This was refined into a nomenclature system by Phirrmann grading both disc height and hydration on MRI . There iCT and MRI scanning demonstrate a range of pathology from internal disc disruption with dehydration changes on MRI, to simple annular disc bulge, associated with degrees of disc space narrowing, Modic endplate changes and facet hypertrophy that eventually leads to foraminal narrowing and entrapment of the nerve root , 4, 6. SStudies have compared the stages and relative size, location, and type of herniated discs to try and predict and guide the surgeon in selecting the type of surgery best suited for the particular patient. These studies attempting to predict outcomes of both conventional and microsurgical disc surgery based on disc size measured on MRI studies have produced inconsistent findings . LocatioThe size of the canal and relative canal compromise has been used to predict need for surgery, outcomes and estimate the clinical impact of radiologic findings . A long-Biomechanics and pathophysiology of the abnormal disc and its relationship to possible surgical proceduresExperimental work on the progressive changes that occur with disc degeneration demonstrate a change in water content with initial expansion or swelling of the nucleus, displacement of the posterior annular wall, followed by annular tears and later disruption of these same annular fibers leading to laxity of the capsule after the disc swelling resolves, or residual sequestered sub-ligamentous disc fragments or disc extrusions -3. The lAnatomic Studies and What They Indicate About Nerve Root EntrapmentAnatomic studies show the disc is not oval, but more kidney bean shaped; and the two thinnest areas of the annulus are the posterior-lateral corners, which is where herniations are most commonly seen . In contThe discectomy systemsThe natural history and evolution of disc herniation is generally in favor of symptomatic resolution; however, the degenerative process may continue while the patient remains clinically asymptomatic. This is supported by many radiologic studies showing increased frequency and levels of progressive radiologic change with age -5, 8-9. Characterization of the Endoscopic and Tubular SystemsAll tubular minimally invasive systems access the disc through the inferior posterior lateral corner of the intervertebral foraminal through what is named ‘Kambin’s Triangle’ -33. GuidWhat amount of abnormal disc nucleus material is necessary to be removed for the best outcomeThe ultimate question is what and how much nuclear material must be removed to get both short-term and long-term improvement in the patient's symptoms. This is also determined by understanding if the main pathology is disc enlargement and annular swelling or root compression from displaced disc and bone. Using a direct visualization endoscopic system, it is possible to visualize the nerve root and make sure it is released from capsular adhesions and fibrosis. After decompression of the root, there should be the return of free pulsations indicating there is no further pressure and root entrapment. In cases with larger disc herniations and fragments, as in open microsurgery, the key step is identifying and visualizing the entrapped nerve root, making sure it is free of fibrous adhesions and any remaining compressing disc fragments, or bony constriction from facet overgrowth -34. SpecVery large disc herniations and even recurrent disc herniations even that have a fragment that has migrated or moved away from the disc space can be approached through tubular endoscopic systems and disc removal. Although it is possible to approach the more posterior and medial part of the disc with an endoscope, the para-median and lateral disc are ideally suited for this approach -38. In tUsing both endoscopic visualization and simultaneous fluoroscopic imaging enables the surgeon to know whether the cannula is properly aligned towards the fragment in the proper direction indicated by MRI. This allows the experienced endoscopic surgeon to approach and remove large and extremely displaced ventral epidural disc fragments, perform a partial facetectomy to free the nerve root within the neural foramina, and remove recurrent discs or place interbody graft material for intervertebral fusion -38. EvenRather than concentrating on the specific tubular instrument system used, the underlying pathology seen on CT and MRI as well as understanding how it relates to the process of disc degeneration and the patient's clinical symptoms should be the focus of the decision regarding the best type of percutaneous transforaminal system to be selected. The more experience the surgeon has with using different systems, understanding their capabilities and limitations of the instruments and how it meshes with the goal of the surgery, allows the maximum use of these minimal surgical approaches and techniques. Over the 30-plus years that tubular and endoscopic systems have evolved, it is clear that many different types of smaller herniated and partially degenerated discs can be effectively and safely de-bulked or removed using these minimally invasive procedures. As these procedures keep evolving, removal of large or migrated disc fragments is more routine. New systems enable the surgeon to do a lateral partial foraminotomy and the possibility to perform interbody fusion. The major advantage of these procedures is complete sparing of damage to the posterior supporting muscles and ligaments, the ability to perform them under local anesthesia with minimal sedation, and in an ambulatory setting. All these elements lead to a faster recovery and preservation of spinal stability. However, the surgeon must also integrate planning the type and severity of the patient's symptoms using the available diagnostic information to identify the specific level and degree of segmental spinal pathology that is creating the patient's problem. It is critical to take into consideration the degree of associated disc space narrowing and facet hypertrophy to guarantee the nerve root is adequately decompressed. The endoscopic surgeon must be able to accomplish this, just as in open surgery, but using minimally-invasive endoscopic procedures that are targeting the disc, disc fragments, and the intervertebral foramina. Proper visualization and release of the entrapped nerve root is a critical step in these procedures.


In the latest years, a lot of research studies regarding the usage of active agents from plants in the treatment of tumors have been published, but there is no data about successful usage of herbal remedies in the treatment of glioblastoma in humans.The phytotherapy involved five types of herbal medicine which the subjects took in the form of tea, each type once a day at regular intervals. Three patients took herbal medicine along with standard oncological treatment, while two patients applied for phytotherapy after completing medical treatment. The composition of herbal medicine was modified when necessary, which depended on the results of the control scans using the nuclear magnetic resonance technique and/or computed tomography.Forty-eight months after the introduction of phytotherapy, there were no clinical or radiological signs of the disease, in three patients; in one patient, the tumor was reduced and his condition was stable, and one patient lived for 48 months in spite of a large primary tumor and a massive recurrence, which developed after the treatment had been completed.The results achieved in patients in whom tumor regression occurred exclusively through the use of phytotherapy deserve special attention.In order to treat glioblastoma more effectively, it is necessary to develop innovative therapeutic strategies and medicines that should not be limited only to the field of conventional medicine. The results presented in this research paper are encouraging and serve as a good basis for further research on the possibilities of phytotherapy in the treatment of glioblastoma. Glioblastoma multiforme falls into the group of astrocytic tumors. It is a most malignant intracranial tumor, and according to the classification by the World Health Organization (WHO), its degree of differentiation is IV [(GBM) grade IV] . AccordiCurrent results achieved in the treatment of GBM are unsatisfactory. The median survival is from 5 months for the patients with primary GBMs to 8 months for those with the secondary GBMs, while a five-year survival is achieved only in about 2% of patients , 5. In tThe use of TMZ in the treatment of GBM is limited by the activity of the gene MGMT (O6-methylguanine-DNA methyltransferase) in tumor cells. This gene encodes an enzyme that effectively repairs the damage caused by TMZ and other alkylating cytostatics used in the treatment of tumors, which significantly reduces their effectiveness .The epigenetic silencing of tumor suppressor genes by the methylation of their promoter is an early event in carcinogenesis, and it leads to the inactivation of these genes, which opens the way to the malignant transformation of the cell .One of tTherefore, a large number of studies that deal with this issue aim at overcoming the problems which, in the treatment of with TMZ and other alkylating agents, cause the activity of MGMT , 13.Unfortunately, for the time being, there is no indication that the results of these studies will lead to any significant breakthroughs in the treatment of GBM, and the modest results in prolonging survival after the introduction of TMZ to the treatment of this tumor are far from the expectations of the patients and their families.Artemisia L. , and the opinion of a pathologist given a few days after the surgery suggested that it was a diffuse astrocytoma (gr II). Following the surgery, the patient was hospitalized in the radiology ward, where 3D conformal radiotherapy was performed by using a linear accelerator with a power of 6 MW. A therapeutic dose of 46 Gy was administered in 23 fractions, followed by radiation of the tumor base with a therapeutic dose of 8 Gy in 4 fractions. With this, the oncological treatment was completed. In August 2012, the patient’s condition deteriorated. At an emergency MRI imaging on 23 August 2012, the progression of the tumor was established, and the dimensions were 46 × 36 mm . On that occasion, an extensive expansive lesion bilaterally and frontally was observed, predominantly on the left side with propagation to the left temporal and left parietal lobe, measuring 90 × 80 mm Fig. . On 27 M mm Fig. . After hStPT was introduced, and she used it in the course of following 6 months. The control MRI imaging performed 3 months after the introduction of StPT (on 21 November 2012) found that tumor progression had stopped Fig. ; therefo2 of body surface area, for 5 days during each cycle. In March 2013, the patient applied for PT and began taking it along with TMZ. A combination of herbal medicines marked as phytotherapy of salvation was immediately introduced. A control NMRI performed in October 2013 showed that there had been a regression of the tumor, with the diameter being 22 mm at the time  was performed in June 2011. The scans showed a well-limited tumor mass without necrosis, located to the left in the frontal parietal-temporal region, measuring 56 × 45 × 51 mm Fig. . A monthime Fig. . The dexime Fig. . Finallyime Fig. . This paDue to persistent headaches and the qualitative alteration of consciousness in a woman aged 58 years, on 11 July 2011, a head NMRI was performed, and it showed an expansive lesion in the left frontal portion of the brain, measuring 60 × 50 × 40 mm Fig. . The tumIn the period between 08 November and 23 December 2011, the patient underwent radiation with 46 Gy, followed by radiation of the tumor base with 14 Gy in 14 fractions. During radiation, the patient had been receiving TMZ in a dose of 120 mg daily for 42 days. Afterwards, 6 cycles of TMZ (240 mg during each cycle) were administered.The patient started to use standard phytotherapy together with combined RT/CT, and then together with monotherapy with TMZ, and continued to use it after the completion of the oncological treatment. She had been taking PT at full capacity and without interruption for 24 months. Five months after the completion of PT, the patient began to complain of an intense headache; so in April 2014, a control NMRI was performed, and a recurrence of the underlying disease in the frontal portion of the head on both sides, in the shape of a butterfly, was found on that occasion. On the right side, prominent was a larger area of 56 × 47 × 43 mm in diameter that occupied the front third of the corpus callosum Fig. .After these findings, the patient was reintroduced to oncological treatment, which consisted of the combined RT/CT followed by planned 6 cycles of monotherapy with TZM in a daily dose of 260 mg for 5 days during a cycle of 28 days. After the third cycle of the treatment with TZM, a control MRI was performed on 04 November 2014, which showed that the dimension of the larger area, located in the right frontal lobe, which occupied the area of the corpus callosum, was 73 × 49 mm Fig. . Due to The patient continued to use standard phytotherapy immediately after the recurrence had been diagnosed. After control imaging performed on 04 November 2014 that showed there had been a progression of the tumor, a PTS combination of herbal medicines was introduced instead of StPT.Control MRI imaging from 26 March 2015 showed that further progression of the tumor had stopped. We should mention that the blocking of tumor growth occurred at the time when PT was the only way of treatment Fig. . In the 2 per day as a “rescue” treatment should be noted as one of the most valuable results, which stop further progression for a period of 6 months in 36% of patients [While in the case of diffuse astrocytoma, after malignant transformation, the standard treatment protocol which is used in primary high-grade astrocytoma is administered; with the progression of primary glioblastoma (GBM), there is no clear strategy of treatment, so the decision on the choice of therapy has to be made by a physician on the basis of the general condition of the patient, the location of the tumor, and previous treatment. As a second-line therapy , chemotherapy with temozolomide (TMZ) had been commonly used, and it is the only effective drug in the treatment of recurrent glioblastoma . The reppatients . In patiHypericum perforatum L. plant can decrease the antitumor drugs and antiepileptic activity [Hypericum perforatum L. This was the only change in the composition of herbal remedies.This paper reveals the use of phytotherapy (PT) in the treatment of five patients suffering from brain tumors who, in addition to varying according to the formation of tumors and the method of treatment, also varied according to the degree of cerebral edema which, how it turned out in the course of this research, significantly affected the effectiveness of PT and was a significant factor that helped to determine the composition of herbal medicines for individual patients. In the course of the research, care was taken not to deprive subjects of the best method of treatment currently used in the treatment of brain tumors in modern medicine. Thus, patients 1, 4, and 5 used PT together with oncological treatment and continued to use it after the treatment had ended, while those patients who completed the oncological treatment (patients 2 and 3) were treated solely with PT. There are some information claiming that pharmacologically active ingredients of the activity . This plThe first two patients whose cases are described in this research paper were continuously treated with a combination of herbal medicines marked as StPT. Among the patients suffering from GBM and high-grade astrocytic tumors in general, there is a difference in the length of survival, and to date, several prognostic factors affecting the survival rate have been identified . IdentifSeveral studies point to pre-surgery tumor size as a significant independent prognostic factor in assessing the length of survival. The trials performed on 510 subjects with malignant glioma, 80% of whom had a diagnosis of GBM, showed that tumor size is a significant prognostic indicator, independent of other prognostic variables .The significance of pre-surgery tumor size with respect to the length of survival was also pointed out in a trial performed on 76 subjects suffering from high-grade astrocytoma, 51 of whom were diagnosed with GBM .1-3max = (a + b + c)/3), which placed her in the group of patients with a poor prognosis and shorter survival expectancy.A mathematical model that took into account the rate of tumor growth and diffusion coefficient predicted that the length of survival of patients with GBM is 158 days on average, which corresponds to the results of the aforementioned trials . The mea3 survive for a significantly shorter period [The extent of cerebral edema at the time of diagnosis represents a significant prognostic factor influencing the time interval of recurrence and the length of survival of patients suffering from GBM, because it suppresses tumor infiltration zone and creates conditions for the migration of tumor cells to portions of the brain that are beyond the reach of surgical procedure and radiotherapy. Therefore, it is considered that the extent of cerebral edema is directly proportional to the presence of tumor cell infiltrates. It should be noted that, due to a shorter period between surgery and recurrence, the patients whose volume of cerebral edema exceeds 75 cmr period .In the first patient, an extensive edema was found by NMRI, and it affected the left hemisphere of the brain almost in its entirety, so that a rapid recurrence had been realistically expected, although it did not happen even after 48 months from the initial diagnosis.Given the pre-surgery tumor size, larger areas of hemorrhagic necrosis, an edema of nearly the entire left hemisphere of the brain, and incomplete oncological treatment, because combined RT/CT had not been followed by monotherapy with TMZ, as well as the poor general condition of the patient, we have a reason to believe that the regression of the tumor residue and long survival of the first subject without the progression of the disease occurred due to the benefits of phytotherapy.Oncological treatment was also not completed in the second patient. It is possible that this was the reason for the recurrence of GBM 4 months after the surgery. After the recurrence, another surgery had been chosen as the second line of defense given that, during the combined RT/CT, the patient had trouble tolerating TMZ, which is the most common choice of treatment in GBM recurrence. Most studies that have dealt with the analysis of the efficacy of a second surgery in the treatment of GBM, including a major trial performed on 208 patients, point out that it does not extend the survival of patients, i.e., that the benefits of a second surgery with respect to GBM for patients are minimal or non-existent . Given tIn the third subject, the progression of tumor occurred soon after RT was completed Fig. , so a neIn this subject, there had been different assessments of tumor grade. A surgical report clearly indicated a highly vascularized tumor, necrotic in its central portion, which suggested it was most likely GBM, and which was confirmed by the extempore analysis. On the other hand, the pathologist claimed that the obtained sample showed no necrosis, that the proliferation of blood vessels was not expressed, and that the proliferative index, measured by Ki-67 antibodies, was low, which led him to the conclusion that it was a diffuse astrocytoma (gr-II).It is known that, inside a tumor, there are often regions with different extent of differentiation and that, in such cases, tumor grade is determined by the least differentiated region. In his report, the surgeon clearly mentioned the presence of necrosis, which is incompatible with the diagnosis of diffuse and anaplastic astrocytoma . In the The progression of tumor shortly after the completion of radiotherapy is an additional argument that, in the case of this patient, the tumor was GBM. Despite an encouraging cessation of tumor growth after the introduction of StPT Fig. , 6 monthThe results achieved with this subject are the most significant part of this paper, not only because of the cessation of tumor progression and its reduction, which occurred exclusively owing to the use of PT, but also because this subsequently introduced combination of herbal mixtures has become a model for the treatment of patients whose tumor is accompanied by a high degree of cerebral edema and those who have an extremely poor prognosis.2 of TMZ a day for 5 days of each cycle.The fourth patient applied for PT after the malignant transformation of previously treated diffuse astrocytoma Fig. . The conPT was introduced together with TMZ. Since the previously described cases showed that StPT has a limited effect on tumors accompanied by a large brain edema, the first choice of treatment for this patient was PTS. The patient started using herbal medicines together with TMZ, which leads to the conclusion that the tumor regression during that time is due to the combined usage of PT and TMZ Fig. . The desHowever, the further reduction of the tumor during the period in which the only method of treatment was PT can be attributed exclusively to herbal medicines Fig. .In the fifth patient, due to the pre-surgery size of the tumor and a large perifocal edema Fig. , a rapidSince there were indications that the previous phytotherapy previously had helped the patient, StPT was reintroduced immediately with a combined RT/CT. After 3 cycles of monotherapy with TMZ and StPT, a control imaging performed in November 2014 showed the progression of the tumor Fig. . After tThe results achieved by introducing PTS in patients 3 and 5 after the progression of the tumor, and the use of PTS in patient 4 as the first choice of treatment, show that this combination of herbal medicines may have a place in the treatment of patients with a poor prognosis. Using standard phytotherapy in the first two patients and partially in patient 5 undoubtedly contributed to their multi-year survival without the progression of the tumor. The efficacy of this combination of herbal medicine can be explained, among other things, by the low extent of cerebral edema after surgery, and it demonstrates that this herbal combination can help those suffering from GBM where cerebral edema does not obstruct the flow of pharmacologically active ingredients to tumor cells.This research paper has shown that oncological treatment and treatment with herbal medicines are not mutually exclusive, which opens the possibility of the simultaneous use of these two methods of treatment.Artemisia L. exposed to the patients in the form of tea. The patients have been following liver markers regularly and not even once this analysis showed a more meaningful growth of the markers.The patients took PT for 24 to 48 months. During the period in which they had been taking PT, regardless of the length of treatment, the patients had no contraindications, nor did the treatment with herbal medicines caused them any problems. Researches about derivative artemisinin hepatotoxicity combined with TMZ have shown that this combination can lead to liver damage . HoweverThe duration of PT is not precisely defined, and the optimal time of its use remains unknown, but it is certain that it should be taken as long as there are clinical or radiological signs of a tumor. Thus, at the time of publication of this research paper, the treatment of patient no. 4 with herbal medicines had not yet been completed, even though 4 years had passed since its introduction. The final results achieved in that patient, but also in other patients whose cases are described in this paper, will be presented as part of the report on the results of the use of PT in the treatment of GBM, which will include a larger number of subjects.This research is still in progress, and it is expected to provide more reliable data on the possibilities of using herbal medicines in the treatment of GBM and to provide answers on the possibility of combined activity of herbal remedies and oncological treatment. The course of this research has greatly been determined by the results presented in this paper, which imposed PTS as the first choice in the treatment of all the patients.The results presented in this paper suggest the possibility of introducing PT as a completely new and harmless method of treating GBM. It is quite safe to conclude that the introduction of PT as a supplementary treatment in patients undergoing oncological treatment or as monotherapy in those cases where the treatment had been completed contributes to the quality of treatment and prolongs the survival of patients. The results achieved in patients in which tumor regression occurred exclusively due to the use of herbal medicines particularly point to such a conclusion.