The tumour microenvironment is shaped by the interaction of tumour cells with a variety of “non” malignant cellular and acellular components. It is the secretion of cytokines, chemokines, metabolites and other mediators in the tumour stroma that shapes the natural evolution of cancer. Whereas the tumour strives to promote an immunosuppressive environment to limit anti-tumour immune response, infiltrating immune cells aim to control tumour growth. The balance between these two conflicting interests shapes the immune contexture of cancer and ultimately patient prognosis. In an effort to characterize the role played by macrophages, we have developed an in vitro system using human pancreatic tumour cell lines and a human monocyte-macrophage leukemic cell line (ThP1). We have investigated the immunosuppressive properties of pancreatic cancer cell lines and how the immune properties of macrophages are influenced by the tumour supernatant in vitro. We have applied our findings to a clinically relevant murine model of pancreatic cancer. We found that, despite some heterogeneity, the profile of MIAPACA-2, BxPC3 and PANC-1, included IL-8, MCP-1, SCF and VEGF secretion. Not surprisingly, when ThP1 cell were cultured in the presence of increasing concentrations of tumour supernatant and stimulated with LPS, we observed a significant downregulation of their ability to produce cytokines associated with an M1 profile . However, ThP1 also failed to display an M2 profile; IL-10 and IL-1ra were similarly downregulated. ThP1 stimulated with LPS in the presence of tumour supernatant also had impaired secretion of a number of other cytokines such as IL-18, MIP-1α and MIP-1β and MCP-1. In contrast, they appeared to maintain secretion of VEGF and IL-7. Next we investigated how the immune stimulant IMM-101, an immunotherapeutic agent comprising heat-killed whole cell Mycobacterium obuense, might be able to shift this anergic phenotype. IMM-101 is currently under clinical evaluation in two Phase II clinical trials in pancreatic (EudraCT number 2010-022757-42) and colorectal cancer (EudraCT number 2011-003958-85). We found that despite the presence of tumour supernatant, macrophages stimulated with IMM-101 retained the ability to secrete the full range of cytokines and we did not observe the impairment reported after LPS stimulation. We believe the immunological properties of IMM-101 make this a potential candidate for successful immunotherapy.


Pulse pressure variation (PPV) is an accurate predictor of fluid responsiveness in mechanically ventilated patients. The aim of this study was the assessment and comparison of the ability of automated PPV, when measured by an IntelliVue MP 70 monitor, and manually calculated PPV to predict fluid responsiveness in mechanically ventilated septic shock patients.We conducted a prospective study on 36 septic shock patients. Automated and manually calculated PPV and other hemodynamic data were recorded before and after fluid administration of 500 ml of 6% hydroxyethyl starch (130/0.4) over 30 minutes. Responders were defined as patients with an increase in their cardiac index >15% after fluid loading.r = 0.79, P < 0.01). Twenty-three (63.9%) patients were classified as fluid responders. Automated PPV and manually calculated PPV were significantly higher in responders than in nonresponders . The area under the receiver operating characteristic curves of automated PPV was significantly greater than the manually calculated PPV . The optimal threshold values for predicting fluid responsiveness were 11% for automated PPV  and 13% for manually calculated PPV .The agreement (mean bias ± SD) between automated and manually calculated PPV was 4.03 ± 7.37%. The baseline automated PPV correlated with the baseline manually calculated PPV (Our results indicate that the automated PPV, obtained by the IntelliVue MP 70 monitor, and manually calculated PPV, showed comparable performance for predicting fluid responsiveness in passively ventilated septic shock patients.


Most consider Twitter as a tool purely for social networking. However, it has been used extensively as a tool for online discussion at nonmedical and medical conferences, and the academic benefits of this tool have been reported. Most anesthetists still have yet to adopt this new educational tool. There is only one previously published report of the use of Twitter by anesthetists at an anesthetic conference. This paper extends that work.We report the uptake and growth in the use of Twitter, a microblogging tool, at an anesthetic conference and review the potential use of Twitter as an educational tool for anesthetists.A unique Twitter hashtag (#WSM12) was created and promoted by the organizers of the Winter Scientific Meeting held by The Association of Anaesthetists of Great Britain and Ireland (AAGBI) in London in January 2012. Twitter activity was compared with Twitter activity previously reported for the AAGBI Annual Conference (September 2011 in Edinburgh). All tweets posted were categorized according to the person making the tweet and the purpose for which they were being used. The categories were determined from a literature review.A total of 227 tweets were posted under the #WSM12 hashtag representing a 530% increase over the previously reported anesthetic conference. Sixteen people joined the Twitter stream by using this hashtag (300% increase). Excellent agreement (κ = 0.924) was seen in the classification of tweets across the 11 categories. Delegates primarily tweeted to create and disseminate notes and learning points (55%), describe which session was attended, undertake discussions, encourage speakers, and for social reasons. In addition, the conference organizers, trade exhibitors, speakers, and anesthetists who did not attend the conference all contributed to the Twitter stream. The combined total number of followers of those who actively tweeted represented a potential audience of 3603 people.This report demonstrates an increase in uptake and growth in the use of Twitter at an anesthetic conference and the review illustrates the opportunities and benefits for medical education in the future. Tweets have a message size limit of 140 characters based on the size of the Short Message Service (SMS) messages used on mobile phones at the time of Twitter’s creation in 2006. Twitter is a technology that still has to be adopted by much of the anesthetic community. Twitter is easily accessed through a number of platforms: the Twitter website, applications (apps) developed for smartphones and tablets, and through SMS from mobile phones (in certain countries). Less than half of the tweets posted are through the Twitter website; most users prefer to use mobile apps on their smartphones or tablets [Twitter  is a mobAlthough most consider Twitter primarily a method of personal communication, it is gaining traction in business and is beginning to be used in academia for many purposes, including rapid sharing and dissemination of information and for citing articles . OrganizThere are only a few published reports of the use of Twitter at medical conferences -12. The The aim of this study was to describe the introduction and uptake of Twitter at a major anesthetic conference with prior involvement and support from the conference organizers and analyze subsequent author use and purpose.A hashtag (represented by the symbol “#”) acts like a metadata tag and can be used for searches of the word/phrase strings it precedes. This makes it possible to quickly and easily collate the tweets being made at a particular conference, and even certain topics at, or subdivisions of, that conference. A hashtag (#WSM12) was created by the AAGBI 6 weeks before the start of their Winter Scientific Meeting held in London in January 2012. This hashtag was actively promoted by the organizers by using their Twitter stream, on posters around the venue, and as part of a PowerPoint presentation shown before each conference session started.All tweets containing the #WSM12 hashtag were recorded. This record was commenced when the hashtag was first advertised and continued 14 days post conference. Any tweets made under the hashtag unrelated to the conference were excluded.The tweets were divided into 3 main sections: (1) before the congress, which included the period from December 3, 2011 (when the hashtag was first advertised) up to 8:59 am on January 18, 2012; (2) during the conference, which included all tweets posted during the conference from 9:00 am on January 18 to 5:00 pm on January 20, 2012; and (3) after the conference, which included any tweets posted under the hashtag from 5:01 pm on January 20 to 12:00 pm on February 4, 2012.The resulting tweets were analyzed to determine who was tweeting, during which time period of the congress they were tweeting, and to categorize the purpose of each tweet. These categories were informed by a literature review ,10,12,14In order to assess internal reliability of the tweet classification, the content of each tweet made during the conference was independently scrutinized by 2 of the authors (DM and GC). Each observer classified each tweet into one of the 11 categories listed in The Twitter profile of each contributor was viewed within 2 days of the end of the conference to record the number of “followers” each tweeter had at that time. Any organizations or individuals specifically mentioned in this paper have been contacted to obtain their consent to display their Twitter profile in this publication.A total of 227 tweets were posted under the #WSM12 hashtag during the 9 weeks of the study period surrounding the AAGBI Winter Scientific Meeting in London. An additional 18 Twitter posts from 12 people were not related to the Winter Scientific Meeting and were excluded from the current analyses. All of the excluded tweets related to a meeting involving Wireless technology usage that also used the #WSM12 hashtag for a brief period, but either changed to an alternative hashtag after realizing the duplication or completed their discussion.Sixteen people contributed to the Twitter stream by using the #WSM12 hashtag. These 16 people consisted of the organizer and the conference venue, 3 members of trade organizations, 3 delegates attending the meeting, and 2 speakers at the meeting. The remaining 6 people who joined the Twitter stream did not attend the meeting and they were either actively promoting the meeting before the conference, contributing to discussion during the meeting, or passively retweeting some of the tweets posted by attendees.The number of followers for each of the people who contributed to the Twitter stream for the #WSM12 hashtag ranged from 3 to 8335 . The 16 P<.001) was seen in the classification of tweets across the 11 categories with agreement of the 2 raters on 95.1% (n=173) of the 182 tweets.Of the tweets posted under the #WSM12 hashtag, 80.5% (182/227) were sent during the conference itself, 14.5% (33/227) were posted before the meeting, and 5.3% (12/227) after the conference ended. Prior to the conference, the conference organizer posted the most tweets. Almost half  of the preconference Twitter stream was to advertise the hashtag and the conference, and 6% (2/33) to promote sessions which would be happening at the meeting. Potential delegates also advertised the meeting and the hashtag and posted 27% (9/33) of the total preconference tweets for this purpose. Another 6% of tweets (2/33) posted related to plans potential delegates were making for the meeting. A member of the anesthetic trade exhibitors also promoted the meeting in a tweet. A speaker posted a tweet promoting a session in which he would be speaking at the congress. Three other organizations used the hashtag to retweet postings advertising the meeting.During the conference, the organizers posted 15.4% (28/182) of the tweets. They used this period of the conference to welcome delegates and advise on registration, promote trade exhibits, and to advise on various sessions and events happening at the meeting including parallel sessions, poster sessions and awards, and social events . The trade exhibitors at the conference posted 2.7% (5/182) of the tweets sent during the meeting to advertise their wares and special events happening at their stands. Speakers posted 1.1% (2/182) of the tweets during the meeting, with one promoting their session and the other advising of attendance and the quality of questions at their session. Anesthetists either attending the meeting, or not attending but directly contributing to the Twitter stream, posted 76.9% (140/182) of the tweets sent during the conference. Over half  of the tweets posted during the actual meeting were notes or learning points from various sessions at the conference. A total of 11.5% (21/182) of the tweets posted described which session people were attending, and 4.4% (8/182) of the tweets were made as a method of discussion between delegates about sessions or previously posted tweets. This discussion was joined by an anesthetist who was not able to attend the meeting. Only 3.3% (6/182) of the tweets posted related to conference social events and interactions. Another 1.6% (3/182) of the tweets related to the poster session, and 1.1% (2/182) provided support for speakers who were about to give a presentation. A total of 3.8% (7/182) of the tweets posted were sent by people not attending the meeting and not actively contributing to the Twitter stream by retweeting messages from the conference. There were no tweets posted which asked questions of any of the speakers.There were 12 tweets posted after the conference. One-third  of the tweets were used to continue discussions started at the conference. A further 4 tweets (33%) were by way of thanks from the organizers, venue, trade, and from an anesthetist who had not attended the meeting, but appreciated the learning points generated in the Twitter stream. Another 3 tweets (25%) promoted the use of the learning points documented within the Twitter stream as a method of reflection for the purposes of revalidation. A further tweet was posted by the organizers to advertise a future meeting .The pattern of tweeting by each of the main groups around the conference is shown in This is the first report to describe the uptake and use of a Twitter stream as an integral part of the communication structure of an anesthetic conference. The total number of 227 tweets posted under the #WSM12 hashtag represents a 530% increase over the 36 tweets that “erupted” spontaneously at the 2011 AAGBI conference as reported by McKendrick . SixteenAlthough the number of people joining the Twitter stream is low , this is in keeping with previous studies surveying academic activity on Twitter . FurtherInternal reliability analyses of our classification of tweets during the conference showed a statistically significant level of intraobserver agreement that suggests that our classification system was robust.There are many ways to use Twitter at a medical conference to enhance the experience for both those at the conference and those unable to attend. Each conference should have a Twitter profile, as should the organizer. These profiles should be promoted well in advance to maximize the number of followers, and the usefulness, of Twitter at the conference. Conference organizers should also agree on a hashtag in advance and publicize it extensively with members. The hashtag should be as short as possible to leave as much of the 140 characters for the message itself.The conference organizers used Twitter effectively during the period before the conference to generate excitement and interest, advertise keynote presenters and workshops, and to guide delegates about registration details as illustrated in Most of the tweets were sent during the congress itself. Twitter usage was not maximized by the organizers to update delegates on last-minute changes or to remind participants of parallel sessions or additional sessions, such as sponsored lunchtime meetings. Attendees at the conference used Twitter to take notes from presentations .The final session of the conference should not be seen as the end of that conference’s Twitter stream. This report demonstrates an enhanced use of Twitter after the congress, with 12 tweets being posted compared to 1 tweet in the 2011 AAGBI conference, as reported by McKendrick . The tweAlthough there are many advantages to Twitter, there are some potential pitfalls. Twitter collects personal information about its users and shares that information with third parties. Third parties can search for characteristics and thereby target users on the basis of their Twitter history and content. Advertisers have even been known to quote users’ tweets in their advertisements . AlthougBy default, all tweets are made public unless an individual changes the settings or sends the message as a direct message. As an individual posting tweets, it is critically important not to broadcast any information or views on Twitter that might conflict with or defame employers, colleagues, students, academics, researchers, and other University stakeholders . AlthougHealth care professionals have concerns about the use of Twitter that need to be addressed, including patient, personal, and other health care professional’s privacy. Such concerns are increasingly being recognized and discussed , and guiIn conclusion, this is the first report to describe the uptake and use of a Twitter stream as an integral part of the communication structure of an anesthetic conference. The usage of Twitter at the 2012 AAGBI Winter Scientific Meeting closely followed trends described for other medical and nonmedical conferences. Therefore, Twitter has potential to be a useful tool at future anesthetic conferences, but there are pitfalls that should be recognized.


The manner in which information is encoded in neural signals is a major issue in Neuroscience. A common distinction is between rate codes, where information in neural responses is encoded as the number of spikes within a specified time frame (encoding window), and temporal codes, where the position of spikes within the encoding window carries some or all of the information about the stimulus. One test for the existence of a temporal code in neural responses is to add artificial time jitter to each spike in the response, and then assess whether or not information in the response has been degraded. If so, temporal encoding might be inferred, on the assumption that the jitter is small enough to alter the position, but not the number, of spikes within the encoding window. Here, the effects of artificial jitter on various spike train and information metrics were derived analytically, and this theory was validated using data from afferent neurons of the turtle vestibular and paddlefish electrosensory systems, and from model neurons. We demonstrate that the jitter procedure will degrade information content even when coding is known to be entirely by rate. For this and additional reasons, we conclude that the jitter procedure by itself is not sufficient to establish the presence of a temporal code. A fundamental question in sensory neuroscience is how information is encoded in spike trains. The question often takes the form of distinguishing between rate codes, in which information is encoded in terms of the number of spikes within an encoding window, and temporal codes, in which the position of spikes within an encoding window carries information beyond that available from the number of spikes in the window An additional consideration is that primary afferent neurons in a variety of sensory systems exhibit an ongoing background discharge. Examples include vestibular afferents To assess the relative importance of firing rate versus precise spike timing in stimulus encoding, a computational procedure is often used in which the time of each spike is “jittered” by the addition of a variable time offset, chosen randomly from a zero-mean distribution However, the distinction between a rate code and a timing code can be problematic for a number of reasons. First, as discussed by Theunissen and Miller linear “black box” whose transfer function is tuned to minimize the mean square error of stimulus estimation. This technique essentially assumes a rate code, since the stimulus is estimated by convolving a spike train with the response function of the optimal linear filter. Adding external noise in the form of jitter is equivalent to a distortion of the transfer function of the optimal filter. Thus, conclusions about the existence of a nonlinear time code drawn solely from application of a linear stimulus reconstruction technique may be questionable.Second, the linear stimulus reconstruction technique Third, the rationale for jitter analysis is based on the assumption that the standard deviation (SD) of the jitter distribution is small relative to the duration of an “encoding window”, so that the number of spikes within the window is unaffected, and only their temporal position within the window is altered. Thus, the SD of the jitter is normally chosen to be much smaller than the characteristic time scale of the stimulus on the assumption that this will be less than the duration of the encoding window. However, since the duration of the encoding window itself is never determined, this assumption cannot be validated, and so the results of artificial jittering should be interpreted with caution.Here, we develop an analytical framework that provides a detailed, quantitative assessment of the effects of artificial jitter on spike train metrics commonly used to analyze sensory encoding: coefficient of variation, serial correlations, power spectral density, transfer functions, and coherence functions. This theoretical analysis allows us to specify precisely the relationships between these metrics as calculated for original and jittered spike trains. Using this framework, we show that jitter alters the higher order statistics of spike trains by introducing spurious serial correlations among interspike intervals. This can alter encoding properties. More importantly, we show that for weak stimuli and linear responses, jitter merely increases the noise in the background discharge. This occurs independently of any applied lower-frequency stimulus, and with minimal effects on stimulus-response gain. The additional noise from jitter results in suppression of the stimulus-response coherence (or the linear reconstruction kernel), and consequently of the mutual information rate, as estimated with the linear reconstruction technique. We illustrate these theoretical results by applying them to a model neuron with gamma-distributed interspike intervals, to a phase model of a periodically firing neuron, and to experimental data from vestibular and electroreceptor afferents. Although we focus on spontaneously active neurons, the theory, results, and conclusions we develop have broad applicability to analyses of sensory encoding.in vitro preparations of red-eared turtles, Trachemys (Pseudemys) scripta elegans, of 10–13 cm carapace length, as in 2/5% CO2. All procedures were approved by the Ohio University Institutional Animal Care and Use Committee (IACUC) (protocol number L01-35). Afferent spikes were recorded with glass micropipettes filled with 2 M NaCl and having electrical impedances of 50–100 MΩ. The electrodes were inserted into the posterior division of the VIIIth nerve along the antero-dorsal margin The activity of vestibular posterior canal afferents was recorded in Polyodon spathula) was recorded in in vivo preparations, as in The spontaneous firing of electroreceptor afferents of paddlefish  is k intervals. The mean firing rate is Three metrics were used to characterize spontaneous discharge: the coefficient of variation of the interspike interval distribution, serial correlation coefficients in ISI sequences, and the power spectral density of a spike train. Given a sequence of spike times m denotes the number of intervening intervals (lags), and ranged from 0 to 100 Serial correlation coefficients (SCCs) are derived from the normalized ISI autocorrelation function, and estimate the average degree to which ISIs are correlated or anticorrelated with other ISIs in the sequence. SCC values were calculated as 2/Hz or simply Hz. The delta functions were approximated by rectangular pulses of height pwelch in the MATLAB Statistical Toolbox) with a 2.048 s Hamming window.Power spectral density (PSD), s(t), is applied to a neuron, and an estimate of the stimulus, cf is the stimulus cutoff frequency. SR coherence is a normalized measure of stimulus-response cross-correlation at different frequencies, defined as: mscohere, with windowing as for PSDs.We used two approaches to assess information encoding in neural responses to external stimuli. The first was a conventional linear reconstruction technique that estimates the lower bound of the mutual information rate, A is the SD of the stimulus, and The quality of the reconstruction is quantified by the coding fraction, m-th and n-th responses, m-th response, and angled brackets indicate averaging over the ensemble of responses. The square root of RR coherence serves as the upper bound of SR coherence, so that the following inequality holds: The second information metric we used was response-response (RR) coherence, which provides an estimate of the upper limit of the mutual information rate A jittered response was obtained by adding independent zero-mean Gaussian random time offsets The derivations of equations used in this section to express the exact relationships between statistical metrics of original and jittered spike trains are given in The coefficient of variation of a jittered spike train is: The serial correlation coefficients of the jittered ISIs, expressed in terms of the SCCs of the original ISI sequence, are given by: The cross-spectral density of a stimulus and a jittered spike train is: The SR coherence of a jittered spike train is: Equations 6–12 are exact and allow an investigator to calculate the metrics of a jittered spike train while bypassing the actual numerical procedure of jittering. For example, Eq. 11 with Eq. 1 allow analytical computation of the lower bound estimate of the mutual information rate for jittered spike trains, based solely on measures of coherence, firing rate and PSD of the original spike train.L, called the order of the gamma distribution, sets its shape, and θ is a scaling parameter. The CV, mean ISI, and the ISI variance are, respectively, In a class of models, we simulated a spike train as a renewal process, i.e., where all ISI durations are independent, with an ISI probability density function (PDF) given by the gamma distribution, L , the PSD shows a sharp peak at a frequency corresponding to the mean firing rate, and smaller peaks at higher harmonics. Thus, for large L, the gamma neuron serves as a simple model of a regularly firing neuron. The special case where For large values of A is the stimulus SD. Using this stimulus for a total duration of 600 s, we numerically generated sequences of ISIs for a rate-modulated gamma distribution.A stimulus, D is the noise intensity. Such a model generates a spike when the phase variable crosses the value of s(t) was identical to the one used for the gamma neuron, i.e. Gaussian, band-limited to below 20 Hz, with SD = A. The equation for ϕ was solved numerically using the explicit Euler method with a time step of 0.01 ms.The dynamics of a periodically firing neuron responding to a stimulus, We developed an analytical framework Methods,  to invesTo set the stage, SR coherence functions for these two afferents illustrate the effects of jitter in the frequency domain. For the PCA, jitter with SD≥10 ms resulted in a significant decrease of SR coherence, but smaller (e.g. 3 ms) jitter had minimal effects . In contILB) was ILB values, and a circles, triangles, ILB by Jitter analysis applied to samples of 10 PCAs and 10 EAs confirmed that, for a given jitter SD, PCAs were less sensitive to jitter than EAs. For the original responses, the lower bound of the mutual information rate .jitter introduces negative serial correlations into ISI sequences that were originally generated by a renewal process. For example, with jitter, the SCC of adjacent ISIs, i.e., where lag, m = 1, becomesεvice versa. This introduction of anti-correlated sequential ISIs can be understood qualitatively as a consequence of the jitter values that are added to spike times being drawn from a distribution with a mean. For any pair of spikes, a large absolute value of jitter added to the first spike time is more likely to be followed by a jitter value closer to the mean being added to the second spike time, due to the phenomenon of regression (reversion) to the mean. Thus, the interval between the spike pair is modified by a pair of numbers that themselves tend to be anti-correlated. Jitter also alters the serial correlation coefficients among ISIs in two different ways. First, the striking result of Eq. 7 is that suppressed by jitter: Second, a quite different effect of jitter is observed for spike trains that are originally generated by a non-renewal process. In this case, the non-zero SCC values of the original spike train are m = 1) for the renewal afferent  for a model neuron with gamma-distributed ISIs, and in asterisk at 44.3 Hz), including one due to the epithelial oscillations (dot at 26 Hz), and peaks at second-order combinations of these fundamentals (44.3±26 Hz)  The power spectrum of a regularly firing neuron has a main peak at a fundamental frequency corresponding to the mean firing rate, and broader peaks at harmonics of the fundamental, as seen in As A non-obvious outcome of our analysis is that, for a regularly firing neuron, even small millisecond-level jitter results in a dramatic increase in PSD power at frequencies below the mean firing rate, if V = 0.05 2 or CV =V = 0.05 2.Small (2–5 ms) jitter caused analogous changes in the PSD of an EA 2, includ Our analytical results provide a clear explanation of this power gain at low frequency, as indicated by the excellent correspondence between numerical results from direct jittering procedures and analytical results from Eq. 9 . To mimic the situation of the mammalian vestibular afferents studied in Sadeghi et al. To demonstrate explicitly that information carried by above, How does stimulus magnitude affect the sensitivity of a spike train to external jitter? For a weak Gaussian noise stimulus alone, the low-frequency power in the spike train will increase with stimulus amplitude and the CV of the spike train will increase quadratically with stimulus SD . The effupper block), spike times varied across stimulus trials because of intrinsic noise in the system, and the jitter has no apparent effect . However, for the stronger stimulus , the phase model's firing was tightly locked to the stimulus so that spike times were synchronized into well-defined temporal patterns, reproduced reliably across the ensemble of stimulus trials. For this stronger stimulus, the 2 ms jitter clearly degraded the spike time synchronization .Finally, we wish to determine if the effects of jitter on linear responses can be dissociated from the effects of jitter on non-linear responses, where precise spike timing carries information in addition to that carried by firing rate. As the amplitude of a stimulus grows, the response of a neuron becomes progressively nonlinear, and a linear encoding model is no longer optimal solid lines), indicating that a linear stimulus encoding model is appropriate. Small (2 ms) spike time jitter resulted in identical and significant reduction of both coherence functions (dotted lines), that was nearly complete by the stimulus cutoff at We quantified the effects of jitter on this cross-trial synchronization by comparing SR and RR coherences for the original and jittered spike trains . For a weak stimulus, SR and RR coherence were essentially identical and can hardly be distinguished in blue solid line) being larger than SR coherence (black solid line) across the whole frequency range. The large values of RR coherence at high frequencies up to 500 Hz, well beyond the stimulus cutoff at upper block). For this nonlinear response, small jitter (SD = 2 ms) affected SR and RR coherence in different ways. There was insignificant suppression of SR coherence (black dotted line) by such small jitter across the entire frequency range, due to the large intra-trial variability of ISIs, that is, their large CV imposed by the stimulus. On the other hand, RR coherence (blue dotted line) was strongly suppressed, but only in the high-frequency band, For a stronger but otherwise identical noise stimulus , the resartificial jitter (noise) to the timing of spikes in a spike train degrades stimulus encoding Spike generation is an inherently noisy process, due to various internal sources of noise in neurons 1. Jitter increases the variability of spontaneous discharges, as measured by the CV. However, jitter also drastically reshapes the correlation metrics of a spike train, e.g. serial correlation coefficients, and the power spectrum. 2. The relative size of jitter is a critical parameter, as jitter reduces stimulus-response coherence in proportion to the ratio of the jitter SD to the intrinsic variability of the neuron's discharge. 3. Jitter reduces both the mutual information rate and the coding fraction of neuronal responses, even in cases where information is linearly encoded. For example, a gamma model neuron with the rate modulated by the stimulus  is sensitive to jitter in the same manner as sensory afferents. 4. For non-linear responses, where spikes are synchronized to stimulus events, small amounts of jitter that have minimal effect on SR coherence can indeed significantly reduce the cross-trial (RR) coherence of repeated responses, and non-linear encoding. Based on these results, we conclude that the degradation of sensory encoding resulting from added spike time noise, as estimated with the linear reconstruction technique, does not provide unequivocal evidence for a temporal code.We have applied this analytical framework to experimental data from turtle vestibular and paddlefish electroreceptor afferents, as well as to model neurons. Our main results regarding the effects of added spike time noise on sensory encoding are: We showed that jitter alters the correlation structure of spike sequences. Jitter introduces negative serial ISI correlations into renewal processes, due to the zero-mean nature of the jitter size distribution. On the other hand, jitter degrades serial ISI correlations that are already present. Such distortions by jitter have not been described previously, but since the distinction between renewal and nonrenewal processes is considered fundamental by computational neuroscientists . Thus, the suppression of information encoding due to artificial jitter can be understood entirely in terms of the relationship between SR coherence and jitter SD. Our analysis shows that for low frequencies and small jitter amplitudes, i.e. when the product of the frequency and the jitter SD is small Click here for additional data file.


Cerebral metastases are the most frequent cerebral tumours. Surgery of cerebral metastases plays an indispensible role in a multimodal therapy concept. Conventional white-light, microscopy assisted microsurgical and circumferential stripping of cerebral metastases is neurosurgical standard therapy, but is associated with an extraordinarily high recurrence rate of more than 50% without subsequent whole-brain radiotherapy. Therefore, neurosurgical standard therapy fails to achieve local tumour control in many patients. The present conceptual paper focuses on this issue and discusses the possible causes of the high recurrence rates such as intraoperative dissemination of tumour cells or the lack of sharp delimitation of metastases from the surrounding brain tissue resulting in incomplete resections. Adjuvant whole-brain radiotherapy reduces the risk of local and distant recurrences, but is associated with a well-documented impairment of neurocognitive function. New surgical strategies, such as supramarginal or fluorescence-guided resection, address the possibility of infiltrating tumour parts to achieve more complete resection of cerebral metastases. Supramarginal resection was shown to significantly reduce the risk of a local recurrence and prolongs two-year survival rates. Furthermore, radiosurgery in combination with surgery represents a promising approach. The incidence of brain metastases appears to be rising, probably due to the improvements in systemic therapy leading to longer survival, an aging patient population, and the now widespread use of magnetic resonance imaging (MRI) . CerebraSurgery plays an indispensable role in the treatment of cerebral metastases, and the benefit of surgery has been documented in numerous studies. However, standard surgical treatment of cerebral metastases is often insufficient in achieving local tumour control, becoming obvious in the high local recurrence rate of surgically resected cerebral metastases without subsequent radiation therapy, which was estimated to be about 50% in some studies , 4. TherToday, in the treatment of cerebral metastases, surgery in combination with subsequent whole-brain radiation therapy (WBRT) is standard protocol. Two hallmark randomised studies from the early 1990s showed the benefit of surgery with subsequent WBRT compared with WBRT alone , 6. A laen bloc resection may be beneficial compared with piecemeal resection for supra- and infra-tentorial situated cerebral metastases. In addition to the type of resection, preoperative tumour volume significantly influences the incidence of local recurrence [en bloc resection should be aspired to, is not possible in all patients when metastases are localised in eloquent-brain areas and are adherent or infiltrate adjacent brain tissue.In order to achieve complete tumour resection and to prevent postoperative neurological deficits, conventional white-light microscopy-assisted microsurgical and circumferential stripping of cerebral metastasis from the surrounding brain parenchyma is employed and has become neurosurgical standard therapy. Furthermore, evidence suggests that an currence –12. HoweStandard procedure of metastasis surgery includes several modern comforts of neurosurgery including: intraoperative use of navigation systems that help in planning the craniotomy; localising the tumour and eloquent structures; and minimising searches for the metastasis within the brain parenchyma, therefore reducing perioperative morbidity, thus improving surgical outcome , 14. IntAs discussed previously, complete surgical tumour resection with low morbidity and mortality is the goal in surgery of cerebral malignancies. Complete surgical resection is important to avoid local recurrences at the original site, as local relapses are most likely caused by incomplete tumour destruction or by intraoperative dissemination of tumour cells, for example, by a piecemeal resection. Therefore, local recurrences of cerebral metastases must be valued as a consequence of failure of the initial therapy.Yoo et al [et al [Local recurrence of cerebral metastases after surgical resection without a subsequent WBRT is frighteningly frequent, and occurred in the range of 70% in older studies . More reoo et al , and coml [et al . From thDespite the urgency of the question, the reasons for which cerebral metastases locally relapse at such a high rate despite complete surgical resection has yet to be fully understood. In addition to intraoperative dissemination of tumour cells by a piecemeal resection technique, the growth pattern of cerebral metastases may be the cause of their local recurrence. Cerebral metastases are widely believed to be sharply delimitated from the surrounding brain tissue and thus easily dissected from adjacent brain tissue, however, newer data suggest otherwise. Invasive growth patterns of cerebral metastases were reported from more than 50% of patients, who underwent brain autopsies . Specialp = 0.001) and at new sites  [p = 0.89) and duration of functional independence [Infiltrating tumour parts and intraoperatively disseminated tumour cells are potentially destroyed by a postoperative radiotherapy, which has shown to be beneficial in several studies. Surgery plus WBRT therapy is superior to surgery as addressed in one prospective randomised trial  and diff= 0.008) . Howeverpendence . About tpendence .Furthermore, the WBRT concept came from a view that there are usually multiple metastases in part not visible by conventional imaging. These metastases will develop at new sites and might be treated by WBRT. In fact, WBRT halved the risk of new metastases at new sites in the EORTC 22952-26001 study, which was 43% and 48% for the surgery and radiosurgery arm, respectively . HoweverWBRT also continues to be problematic, bearing severe side effects such as radiation-induced neurocognitive impairment with an acute neurocognitive impairment and a delayed irreversible decline of neurocognitive function . NeurocoBesides, the use of monoclonal antibody is a hallmark approach, improving therapy and prognosis of patients suffering from malignant diseases. Nevertheless, development and evaluation of new invasive and non-invasive treatment regimes for cerebral metastases are urgently required and may ultimately reduce the necessity of WBRT, which so often comes in hand with neurocognitive deficits.5-Aminolevulinic acid (5-ALA)-derived fluorescence-guided resection was introduced in surgery of malignant gliomas about a decade ago. This technique was shown to enable more complete resections of malignant gliomas and improve local tumour control and six month progression-free survival compared with conventional white-light resection –32. 5-ALet al. analysed 5-AIF in a small series of 11 metastatic brain tumours and found 5-AIF in 9/11 patients (82%) [Initially, Utsuki ts (82%) . This obts (82%) . Howeverts (82%) .Both studies also analysed fluorescence of the tumour cavity after white-light assisted, macroscopically complete tumour resection, and evaluated the impact of 5-AIF in the detection of possible infiltrating tumour parts. Utsuki and colleagues observed 5-AIF not only in peritumoural but also in tumour-free oedematous tissue and assumed an unspecific protoporphyrin IX leakage . In the As the majority of intracerebral metastases exhibit 5-AIF fluorescence, this method could improve visualisation of the surgical target. The intense fluorescence of the peritumoural adjacent brain tissue, even of metastases with little or no 5-AIF, may prove useful in locating tumour tissue. However, cerebral metastases themselves display regionally heterogeneous and unpredictable 5-ALA-induced fluorescence patterns, which do not correlate with histopathological findings. Also, reliable identification of infiltrating tumour parts appears to be problematic, as fluorescence of the adjacent brain tissue correlated with histopathological verification of tumour tissue in only one-third of patients. Therefore, 5-AIF of the adjacent peritumoural brain tissue should be interpreted with great caution.et al. [p = 0.003; two-year recurrence rates were 29.1% and 63.2% for the supramarginal resection and control group, respectively) [p = 0.0001) [One key study analysing new approaches in the surgery of cerebral metastases was performed by Yoo et al. . Supramactively) . Suprama 0.0001) . Further 0.0001) .en bloc resection may be beneficial compared with piecemeal resection. Nevertheless, local recurrence of cerebral metastases after surgical resection without subsequent WBRT is frighteningly frequent (more than 50%) after complete surgical resection. Explanations for these high recurrence rates may be an intraoperative dissemination of tumour cells, or the lack of sharp delimitation of the metastasis from the surrounding brain tissue resulting in incomplete resection. WBRT reduces the risk of a local recurrence but comes at a very high cost. Supramarginal resection of cerebral metastases , and radiosurgery in combination with surgery represent promising approaches and may prove essential in improving treatment of cerebral metastases.Although surgery has proven indispensible in the treatment of cerebral metastases, new surgical techniques in combination with noninvasive methods are necessary in enhancing tumour control. Conventional white-light microscopy-assisted microsurgical and circumferential stripping of cerebral metastasis from the surrounding brain parenchyma remains standard as fluorescence-guided resection does not appear to be reliable in identifying infiltrating tumour parts. Furthermore,


Caenorhabditis elegans. maco-1 mutants showed abnormal behaviors, including defective locomotion, thermotaxis, and chemotaxis. Expression of human macoilin in the C. elegans nervous system weakly rescued the abnormal thermotactic phenotype of the maco-1 mutants, suggesting that macoilin is functionally conserved across species. Abnormal thermotaxis may have been caused by impaired locomotion of maco-1 mutants. However, calcium imaging of AFD thermosensory neurons and AIY postsynaptic interneurons of maco-1 mutants suggest that macoilin is required for appropriate responses of AFD and AIY neurons to thermal stimuli. Studies on localization of MACO-1 showed that C. elegans and human macoilins are localized mainly to the rough endoplasmic reticulum. Our results suggest that macoilin is required for various neural events, such as the regulation of neuronal activity.Neural signals are processed in nervous systems of animals responding to variable environmental stimuli. This study shows that a novel and highly conserved protein, macoilin (MACO-1), plays an essential role in diverse neural functions in  Caenorhabditis elegans can sense diverse environment stimuli using a nervous system that consists of only 302 neurons. C. elegans exhibit thermotaxis that allows them to remember ambient temperatures and use this information as a cue to seek and remain near food sources. We show here that a novel and conserved protein, MACO-1, is important for proper execution of thermotaxis by C. elegans. The maco-1 gene was originally identified in a novel thermotaxis-defective mutant. Abnormal thermotaxis of maco-1 mutants was weakly but apparently rescued by expressing human MACO-1, suggesting that MACO-1 is functionally conserved among species. MACO-1 protein is required for appropriate regulation of neuronal activity, and the activity of neurons required for thermotaxis is impaired in maco-1 mutants. This analysis provides an important basis for the function of the macoilin family.Any animals, including humans, have to be capable of properly sensing and responding to various environmental stimuli for survival and reproduction. Environmental stimuli are evaluated and, based on past experiences, converted to produce appropriate adaptive behaviors. Even the small, free-living soil nematode  Drosophila melanogasterCaenorhabditis elegansC. elegans, more than 40 percent of the predicted protein products show significant matches to those from other animals Genome projects have determined DNA sequences of various organisms and identified locations of predicted genes in genomes. Surprisingly, numbers of genes are relatively similar across evolutionally divergent animal species. For example, estimated gene numbers are 20000–25000 in human C. elegans is composed of only 302 neurons C. elegans can sense an array of environmental stimuli and produce appropriate behavioral outputs. For example, worms remember cultivation temperatures in association with food conditions C. elegans with food at a certain temperature for several hours, they will migrate to this cultivation temperature along a temperature gradient C. elegansncs-1 animals could be rescued by introducing a wild-type NCS-1 into the AIY interneuron, which is a component of the thermotaxis neural circuit, and that NCS-1 overexpression enhanced the frequency of IT behavior Animals use the nervous system to detect stimuli in the surrounding environment. These stimuli are then assessed based on past experiences, and converted into adaptive behaviors. Many neurons are required to act in coordination to execute these processes. However, it is difficult to address individual neuronal function in relation to other neurons in neural circuits because animal brains generally consist of enormous numbers of neurons. The anatomically characterized nervous system of C. elegans, which was achieved by laser-ablating specific neurons, has been examined previously, and results led to the hypothesis of a neural circuit for thermotaxis The thermotaxis phenotype of C. elegans. maco-1/ttx-8 mutants exhibited abnormalities in thermotaxis and chemotaxis to odorants and sodium chloride (NaCl). The maco-1 gene encodes a conserved novel protein that is expressed in many neurons. A previous study reported that the mouse ortholog of MACO-1, macoilin (C61), showed neuron-specific expression maco-1 mutants is required for thermotaxis behavior. We also found that maco-1 mutants showed abnormal locomotion resulting from frequent turns. Although defective locomotion of maco-1 mutants might have caused abnormal thermotaxis, calcium imaging indicated that MACO-1 is required for activation of AFD and AIY neurons. In vivo co-localization studies have shown that both MACO-1 and human macoilin are localized to the rough endoplasmic reticulum (rER). All together, our results suggest that macoilin is required for a variety of intracellular events that influence basic neuronal function across species.In this study, we found that the novel protein MACO-1 is required for diverse neuronal functions in maco-1(nj21) and maco-1(nj34), were isolated as novel mutants. Two other mutant alleles, maco-1(tm2917) and maco-1(ok3165), were isolated by the National Bioresource Project (Japan) and the C. elegans Gene Knockout Consortium, respectively. All four alleles were genetically recessive (data not shown). Despite obvious defects in thermotaxis after cultivation at 20°C (maco-1(nj21) and maco-1(nj34) mutants were slightly defective in chemotaxis to odorants  than 17°C or 23°C TTX assays. Specifically, during 20°C TTX assays, animals must migrate and remain in the 20°C region, which is shown as the light grey zone in the left schematic of To elucidate molecular mechanisms of thermotaxis, we performed a genetic screen and isolated several mutants that were thermotaxis defective  at 20°C , maco-1(odorants  or to Naodorants . These rmaco-1 gene was identified by mapping it with the snip-single nucleotide polymorphisms (SNPs) method maco-1 mutants was rescued by introduction of the cosmid C09C9. However, thermotaxis was not rescued by the cosmid C15E12 or C03F5  did not rescue abnormal thermotaxis behavior of maco-1 mutants. However, another PCR fragment containing D2092.5 gene (PCR2) could rescue this behavior  and a missense mutation (A805T) (tm2917 mutant has a 780-base pair (bp) deletion and 1-bp insertion just before the first coiled coil domain  . The tm2l domain . The ok3l region .almost full-length genomic maco-1::GFP, which can rescue abnormal thermotaxis of maco-1 mutants .To study subcellular localization of MACO-1, we introduced the  mutants , into wi mutants . Because mutants . Similar mutants . Further mutants , and CFP mutants . These rmaco-1, we constructed the maco-1 promoter::GFP reporter that used an approximately 5-kilobase (kb) upstream region from the ATG initiation codon as a maco-1 promoter. This construct was then introduced into wild-type animals. We found that strong expression was observed in many neurons  mutants to thermal stimuli. We found that the ratio change in AFD neurons of maco-1(nj34) mutants was significantly less than that of wild-type animals (tax-4(p678) mutants was hardly detected tax-4(p678) mutant do not respond properly to temperature because of defective cGMP-dependent cation channels composed of TAX-2 and TAX-4. The average of maximum ratio change from baseline ± SEM in maco-1(nj34) mutants was slightly larger (4.3±0.8) relative to tax-4(p678) mutants (3.3±0.6) maco-1(nj34) mutants was not completely lost but partially reduced. Similarly, the ratio change in AIY neurons of maco-1 mutants was also lower than that of wild-type animals  is localized to the ER and required for the maturation  of nicotinic acetylcholine receptors maco-1 mutants. We found slightly increased spacing between adjacent SNB-1::GFP puncta (presynaptic marker) in DD motor neurons of maco-1 mutants compared with wild-type animals  I, IK734 maco-1(nj34) I, IK809 maco-1(tm2917) I, IK811 maco-1(ok3165) I, N2; Is[flp-13p::snb-1::gfp] II maco-1(nj21) and maco-1(nj34) mutants were isolated in genetic screens that bypassed temperature-dependent dauer formation of daf-7(e1372) backgrounds 4), 1 mM calcium chloride (CaCl2) and 25 mM potassium phosphate (pH 6)). Dilutions of odorants with ethanol were as follows: 1∶1000 diacetyl, 1 mg/ml pyrazine, 1∶100 isoamyl alcohol, and 1∶100 benzaldehyde. The chemotaxis index was calculated according to Bargmann et al. Animals were grown at 20°C for all behavioral assays in this study, unless otherwise described. The procedure for the thermotaxis assay using radial temperature gradients was based on previously published research by Mori and Ohshima maco-1 promoter::GFP (pMYA3) used in maco-1 promoter region . This fragment was then inserted into the GFP vector pPD95.77 to generate pMYA3. The almost full-length genomic maco-1::GFP (pMYA52) was constructed by PCR amplification of the 5′ 5-kilobase (kb) region of maco-1 gene and 2-kb fragment downstream of 5′ 5-kb fragment using the cosmid C09C9 and wild-type genomic DNA, respectively. These fragments were inserted between the maco-1 promoter and GFP of pMYA3 to generate the almost full-length genomic maco-1::GFP (pMYA52). The almost full-length genomic maco-1 contains a maco-1 promoter region and a 6621-bp fragment of a 7536-bp full-length genomic maco-1 sequence, which includes predicted transmembrane domains and coiled coil domains. The full-length maco-1 cDNA was constructed by PCR amplifications of the 5′ partial maco-1 cDNA (723-bp region of 2694-bp full-length maco-1 cDNA) and the rest of maco-1 cDNA region using a cDNA library and yk1296a05 clone, respectively. These fragments were ligated into pPD49.26 to generate pMYA17. All cell-specific promoter::maco-1 cDNA plasmids were generated by inserting each cell-specific promoter fragment into pMYA17. Cell-specific promoters are as follows: unc-14p for almost all neurons gcy-8p and gcy-18p for AFD neurons ttx-3p for AIY neurons lin-11p for AIZ neurons (unpublished data); odr-1p for AWC neurons glr-3p for RIA neurons (unpublished data). Detailed expression patterns of these cell-specific promoters are shown in maco-1 cDNA and several organelle markers used in glr-1 promoter of glr-1p::YFP::TRAMgcy-8 promoter to generate gcy-8p::YFP::TRAM (pMYA161). The TRAM of pMYA161 was replaced with maco-1 cDNA to generate gcy-8p::YFP::maco-1 (pMYA174). The YFP of pMYA161 was replaced with CFP to generate gcy-8p::CFP::TRAM (pMYA212). The TRAM of pMYA161 was replaced with FLJ10747 cDNA to generate gcy-8p::YFP::FLJ10747 (pMYA182). The glr-1 promoter of glr-1p::MANS::YFPgcy-8 promoter to generate gcy-8p::MANS::YFP (pMYA145), and then YFP of pMYA145 was replaced with CFP to generate gcy-8p::MANS::CFP (pMYA208). The glr-1 promoter of glr-1p::YFP::GPIgcy-8 promoter to generate gcy-8p::YFP::GPI (pMYA153). The glr-1 promoter of glr-1p::CFP::PISgcy-8 promoter to generate gcy-8p::CFP::PIS (pMYA141). The PIS of pMYA141 was replaced with maco-1 cDNA to generate gcy-8p::CFP::maco-1 (pMYA176). Two types of truncated forms of MACO-1, MACO-1 TM (1–453 amino acid) and MACO-1 CC (446–897 amino acid) (unc-14p::maco-1 cDNA and replaced with full-length maco-1 cDNA of unc-14p::maco-1 to generate unc-14p::MACO-1 TM (pMYA107) and unc-14p::MACO-1 CC (pMYA109), respectively. The unc-14p::FLJ10747 shown in unc-14 promoter into pPD49.26 vector to generate pMYA171. The full-length cDNA of human macoilin, FLJ10747 cDNA, was PCR amplified from a Mammalian Gene Collection (MGC) clone (Invitrogen), which contained full-length FLJ10747 cDNA. This product was inserted into pMYA171 to generate unc-14p::FLJ10747 (pMYA172).The no acid) , were PCalmost full-length genomic maco-1::GFP used in gcy-8p::YFP::maco-1 (pMYA174) (20 ng/µl) and gcy-8p::CFP::TRAM (pMYA212) (20 ng/µl) into wild-type animals. This injection was coupled with 120 ng/µl of pTAN124.5 (ges-1p::DsRed) as a co-injection marker. gcy-8p::YFP::FLJ10747 (pMYA182) (50 ng/µl) and gcy-8p::CFP::TRAM (pMYA212) (4 ng/µl) were co-injected into wild-type animals with ges-1p::DsRed (pTAN124.5) (120 ng/µl) as a co-injection marker. ges-1p::NLS-GFP (pKDK66) maco-1(nj34) at 2 and 50 ng/µl, respectively.Transgenic strains were constructed by injecting DNA into the gonad of adult animals Animal behavior was recorded using a custom made tracking and live imaging system. Well-fed single animal was placed on a TTX plate for tracking experiments. An ordinal analog video camera (Olympus) captured freely moving individual animal for 30 min with adequate sampling rate (30 frames/sec). A computer-controlled microscope stage was automatically moved to center animals in the visual field using a custom image analysis algorithm with microscope software . Midlines of recorded animals were extracted from each image, and curvatures at certain positions were calculated by analyzing points along midline with constant intervals. Spatio-temporal curvature maps were constructed by expressing the quantity of curvatures with a color-map . A smoothing filter (3×3 dimensions) was applied to the curvature map to reduce noise effects. Omega turn states  and AIYp::yc3.60 (pNR86.79), were glued onto a 2% agar pad on glass, immersed in M9 buffer, and covered by cover glass. The agar pad and M9 buffer were kept at the initial imaging temperature. Sample preparation was completed within one minute. The sample was then placed onto a Peltier-based thermocontroller  on the stage of a Nikon E600 or Olympus BX61WI microscope at the initial imaging temperature for two minutes. Fluorescence was introduced into W-View  or Dual-View  optic systems. Cyan fluorescent protein  and yellow fluorescent protein  images were simultaneously captured by a CCD camera HiSCA or EM-CCD camera C9000-13 ImagEM (Hamamatsu Photonics). Images were taken with a 200-ms exposure time with 4×4 or 2×2 binning. Temperatures on the agar pad were monitored by the thermometer system, DCM-20 (Tokai Hit and Hamamatsu Photonics). For each imaging experiment, fluorescence intensities of F535 and F480 were measured using AquaCosmos (Hamamatsu Photonics) or MetaMorph (Molecular Device) imaging analysis systems. Relative increases or decreases in intracellular Ca2+ concentrations were measured as increases or decreases in YFP/CFP fluorescence ratios of cameleon protein (ratio change).Error bars in figures indicate standard errors (SEM). The statistical analysis for behavioral experiments was performed by one-way analysis of variance (ANOVA) for multiple comparisons followed by post hoc Dunnett's multiple comparison. A single asterisk and double asterisk indicate statistical significance at p<0.05 and p<0.01, respectively. The value of p is probability.Figure S1maco-1(nj21) or maco-1(nj34) and index of wild-type at each concentration. One asterisk denotes statistical significance at the p<0.05 level and two asterisks denote statistical significance at the p<0.01 level (ANOVA with a Dunnett's post hoc test).Chemotaxis to odorants. (A) Chemotaxis to diacetyl with varying dilutions. (B) Chemotaxis to pyrazine with varying dilutions. (C) Chemotaxis to isoamyl alcohol with varying dilutions. (D) Chemotaxis to benzaldehyde with varying dilutions. Error bar indicates the standard error of the mean (SEM). Asterisks indicate statistically significant differences between the index of (0.26 MB TIF)Click here for additional data file.Figure S2maco-1(nj34) mutants. (A–C) All animals tested were cultivated at 20°C. The y-axis shows the fraction of 20 animals that migrated to the 20°C region. Error bar indicates the standard error of the mean (SEM). (A) Expression of almost full-length genomic maco-1::GFP (50 ng/µl) in most neurons of maco-1(nj34) mutants rescued the abnormal thermotaxis phenotype of maco-1. Statistical significance could not be described due to insufficient assay numbers (two). However, there was an obvious difference between the fraction of 20 of maco-1(nj34) and that of maco-1(nj34); Ex[almost full-length genomic maco-1::GFP] strain . (B) Rescue experiments with varying concentration of FLJ10747, human maco-1 cDNA . Single and double asterisks indicate fractions of 20 of each transgenic strain that was different from fraction of 20 of maco-1(nj34) mutants at the p<0.05 and p<0.01 level, respectively (ANOVA with a Dunnett's post hoc test). (C) n = 60–120 animals. Double asterisks indicate the fraction of 20 of maco-1(nj34); Ex[unc-14p::YFP::maco-1] strain that were different from that of maco-1(nj34) mutants at the p<0.01 level (ANOVA with a Dunnett's post hoc test).Rescue experiments for thermotaxis defects in (0.34 MB TIF)Click here for additional data file.Figure S3maco-1 promoter::GFP (pMYA3) in wild-type. DIC and GFP images are merged. Anterior is to the left. GFP expression was observed in many neurons. Names of several neurons are shown.  Expression of GFP in AFD and AIY neurons. (B) Wild-type. (C) maco-1 mutants. Left panels show merged DIC and GFP images and right panels are GFP images alone. A yellow arrowhead and white arrowhead indicate the cell body of AFD and AIY neurons, respectively. Yellow arrows show dendrites (left side of the yellow arrowhead) and axons (right side of the yellow arrowhead) of AFD neurons. A white arrow shows an axon of AIY neurons. Scale bars = 5 µm.Expression pattern of MACO-1 and neuronal morphology of AFD thermosensory neurons and AIY ineterneurons. (A) Expression of (1.93 MB TIF)Click here for additional data file.Figure S4maco-1(nj34) animals. This transgenic strain showed a partial-rescued phenotype (maco-1(nj34). This strain did not show the rescued phenotype (maco-1(nj34). This strain showed little to no rescued phenotype ::MACO-1, YFP::MACO-1 TM, and YFP::MACO-1 CC. (A–C) Expression of YFP::MACO-1 in almost all neurons and cyan fluorescent protein (CFP)::TRAM (rER marker) in AFD neurons of henotype . (A) YFPhenotype . (J) Merhenotype . (L) Mer(3.51 MB TIF)Click here for additional data file.Figure S5maco-1 mutants. (A–D) SNB-1::GFP expression in six DD motor neurons of L2 larva. We observed transgenic strains, N2; Is[flp-13p::SNB-1::GFP] maco-1(nj34); Is[flp-13p::SNB-1::GFP]. The expression pattern of flp-13p::GFP was shown in maco-1(nj34) mutant.  Arrowheads show cell bodies of DD2, DD3 and DD4 motor neurons. (E) Quantification of distance between adjacent puncta. We measured the distance between adjacent puncta and categorized it into sixteen classes. The x-axis and y-axis show each class and fraction of distance categorized into one of sixteen classes, respectively. Error bar indicates the standard error of the mean (SEM). The statistical difference was determined by using a two-tailed Student's test. A single asterisk indicates statistically significant difference at p<0.05. n = 27 (wild-type) and 30 (maco-1).Slight mislocalization of presynaptic marker, SNB-1::GFP, in (1.42 MB TIF)Click here for additional data file.Table S1Homology search. Results of a homology search by Blast using amino acid sequences of MACO-1 or human homolog of MACO-1 as queries. Several molecules of vertebrate or invertebrate are shown for each survey. The identity and similarity are calculated using the software program, Mac vector.(0.04 MB DOC)Click here for additional data file.Table S2lin-11p as an AIZ promoter, glr-3p as a RIA promoter and odr-1p as an AWC promoter Click here for additional data file.Text S1Supplemental (0.05 MB DOC)Click here for additional data file.


Knowledge of natural tumour growth is valuable for understanding tumour biology, optimising screening programs, prognostication, optimal scheduling of chemotherapy, and assessing tumour spread. However, mathematical modelling in individuals is hampered by the limited data available. We aimed to develop a method to estimate parameters of the growth model and formation rate of metastases in individual patients.Data from one patient with liver metastases from a primary ileum carcinoid and one patient with lung metastases from a primary renal cell carcinoma were used to demonstrate this new method. Metastatic growth models were estimated by direct curve fitting, as well as with the new proposed method based on the relationship between tumour growth rate and tumour volume. The new model was derived from the Gompertzian growth model by eliminating the time factor (age of metastases), which made it possible to perform the calculations using data from all metastases in each patient. Finally, the formation time of each metastasis and, consecutively, the formation rate of metastases in each patient were estimated.With limited measurements in clinical studies, fitting different growth curves was insufficient to estimate true tumour growth, even if patients were followed for several years. Growth of liver metastases was well described with a general growth model for all metastases. However, the lung metastases from renal cell carcinoma were better described by heterogeneous exponential growth with various growth rates.Analysis of the regression of tumour growth rate with the logarithm of tumour volume can be used to estimate parameters of the tumour growth model and metastasis formation rates, and therefore the number and size distribution of metastases in individuals. Studying natural tumour growth is valuable for understanding tumour biology, optimising screening programs, prognostication, optimal0 and t, the following equation is valid[The exponential model is a simple growth model of solid tumours. Assuming exponential tumour growth, the growth rate can be calculated from tumour volume measurements from at least two occasions, either as the tumour volume doubling time (DT) or the specific growth rate (SGR). DT is tis valid:The above equation shows that SGR is equivalent to the exponential growth constant of the tumour. In other words:1 and t2, then the SGR of the tumour during the period of observation can be calculated as:If tumour volume is measured on two occasions, t1 and V2 are the tumour volume at t = t1 and t2, respectively. SGR is reciprocally related to DT as follows:where VWe have previously demonstrated that SGR is less affected by measurement uncertainties than DT, and is a better variable to characterise tumour growth rate,6.According to the exponential model, the tumour’s SGR is constant and independent of tumour volume. However, studies have shown that tumour growth rate may decline with time-9 .where SGRThe standard method to find the growth model that best describes tumour growth is direct curve fitting. Exponential and Gompertzian growth curves are fitted to the volume of each tumour, and the model with the best fit is selected. Using direct curve fitting with the Gompertzian model requires at least three data points per tumour. However, in clinical studies, therapy is usually initiated soon after diagnosis; therefore, the natural tumour growth patterns can only be followed for a limited time before the onset of treatment. Thus, clinical observations of growth rate decline in tumours  are very rare, and the exponential model is most commonly used.The aim of this study was to develop a new method to estimate the parameters of the non-exponential growth model for metastatic tumours in patients. To demonstrate the applicability of the new proposed method, we applied the method to data from one patient with liver metastases arising from a primary ileum carcinoid and one patient with lung metastases arising from a primary renal cell carcinoma.Data from two patients were used in this study. The first patient was diagnosed with primary midgut carcinoid and liver metastases. The primary tumour was surgically resected in 1995. Growth data were obtained from eight computed tomography (CT) examinations performed annually during 1995–2002. During this period, the patient was treated with octreotide  for hormonal symptom relief, and interferon alfa-2b  was administered on three occasions without clinical response. The volume of each tumour was measured by point counting: a transparent paper marked with square millimeters was used to measure the tumour area in CT slices, and the tumour volume in the slice was estimated by multiplying the tumour area by the slice thickness. The total tumour volume was calculated as the sum of tumour volumes from the individual CT slices.http://www.osirix-viewer.com/). Each tumour was assumed to be equal to the volume of a sphere with the diameter of a circle with the same area as the estimated tumour area in the radiograph. Because the lining border of the tumour could not be clearly defined in all images, the number of available data points may vary for different metastatic tumour masses.The second patient was diagnosed with primary renal cell carcinoma with lung metastases. Renal cancer is notoriously chemotherapy resistant. During the 1980th biological therapy with interferon with few responses, but considerable toxicity, was introduced and in the 1990th also IL2 was added, again with modest efficacy but with significant side effects. Due to All CT and X-ray imaging data used in this study concern deceased persons and were retrieved retrospectively from the patient imaging database at Sahlgrenska University Hospital, Gothenburg, Sweden. This type of information on deceased persons is exempt from ethical approval according to the Ethical Review Act in Sweden (2003:460).We first attempted to estimate the growth model of each tumour by direct curve fitting, where it was not possible to select the most probable growth model of each metastasis directly. However, exponential growth rates were higher for smaller tumours than for larger tumours, possibly as a result of growth deceleration as tumours grow (the Gompertzian growth model). Therefore, we developed a new mathematical method assuming that, in each patient, the smaller metastases represent the growth of larger metastases when they were of small size and vice versa. Based on this assumption, all metastases of the same type, in the same tissue and in the same patient, follow a general Gompertzian growth model; variations in growth rates are because of volumetric differences. If the time of formation of each metastasis were available, it would be possible to estimate the parameters of such a general Gompertzian model by fitting the Gompertzian curve to data from all metastases in a single curve fitting. However, the formation time of each metastasis can, in turn, be estimated only if the growth model of the metastasis is known. Therefore, we reformulated the Gompertzian curve  by eliminating the time parameter. From Equations 2 and 5, the relation between SGR and tumour volume is as follows (see Appendix A):0 and λ) can be estimated using the linear regression parameters in Equation 6.Equation 6 does not include time, which makes it possible to use data from all metastases of the same type in a single patient without knowing the age of each individual tumour. Equation 6 shows that the regression of tumour SGR with the logarithm of its volume is linear if the growth model is Gompertzian. Therefore, the parameters of the general Gompertzian growth model of metastasis in each patient . (4) Equation 5 with the estimated λ and SGR0 values (from stage 3) was assumed to represent the general Gompertzian growth curve of all metastases in each patient. According to this assumption, the general growth curve can describe the growth of each metastasis when the time origin is changed . Therefore, (5) the general growth curve was fitted to the volume of each metastasis with time origin as a variable, and the formation time of each metastasis was estimated using the best fit for each tumour.This method was applied to our patient data as follows. (1) SGR values were calculated for each metastasis, using Equation 3 for each pair of consecutive tumour volume measurements. (2) The logarithm of the geometric mean of the two volumes (used in stage 1) was calculated for each pair of consecutive tumour volume measurements of each metastasis. (3) Using all SGRs (stage 1) and volumes (stage 2) from all metastases in each patient, λ and SGRAll curve fittings were performed using Matlab 6.5.1 with the curve fitting toolbox .2 values  and, therefore, not realistic. For the best exponential fits, the SGR values were 0.14-0.33%/day for liver metastases  or in the lungs, was well described by either the exponential or the Gompertzian model with high rs Table . Liver m0) differed by an order of magnitude: 0.14%/day and 1.1%/day with the exponential and the Gompertzian models, respectively. These values correspond to DT values of 17 months and 2 months, respectively.Figure 2 = 0.33, p < 0.005), and the estimated λ and SGR0 values were 0.00023 and 0.79%/day, respectively  can describe the growth of all tumours. Lack of correlation between SGR and the logarithm of tumour volume indicates that biological factors other than growth deceleration dominate the observed growth rate variations. Thus, these tumours may grow exponentially with different growth rates or according to the Gompertzian model, but the model constants (SGR0 and λ) are heterogeneously distributed among tumours.In the proposed method, a significant negative correlation between SGR and the logarithm of tumour volume indicates that growth deceleration is a dominating factor in the observed growth rate variations. In other words, the smaller tumours represent the growth of larger tumours when they were of small size and vice versa, and a general Gompertzian growth model . The model described well the increase of the number of metastases growing exponentially with different growth rates, or growing according to a general Gompertzian model. This finding is similar to the results of a previous study that employed a different approach.Our results showed that a decelerating growth model such as the Gompertzian model implies a higher metastasis formation rate than the exponential model. However, a higher metastasis formation rate does not necessarily mean a larger number of metastases at any time point, and the number of metastases should be calculated for any specific time to compare different models. The time origin in Figure We evaluated the Gompertzian growth model in the present study because it is the most commonly adopted model in clinical studies,8; howevAnalysis of the regression of tumour growth rate with its volume can be used to estimate the non-exponential growth model parameters of metastatic tumours. These results are valuable for the optimisation of targeted radionuclide therapy based on the estimated number and size distribution of metastases in individual patients.Relation between tumour growth rate and tumour volumeFrom Equation 5 (Gompertzian model):andReplacing the left side of the above equation with Equation 2 gives:orIf exp (−λt) in Equation 7 is replaced by the above equation, then:Readjustment of the above equation gives Equation 6 in the article:where SGR is the value of tumour SGR at each period of observation  and V is the geometric mean of tumour volume at that period of observation.0 and volume of a tumour at time t = 0 are 0.1%/day (= 0.001 day-1) and V0 = 1 (arbitrary unit), respectively. The tumour grows according to the Gompertzian model with λ = 0.0003 day-1. Tumour volume is measured every six months (180 days). The last two columns in Table 2 show the calculated logarithm of the geometric mean of tumour volume and the tumour SGR at each consecutive pair of measurements, respectively:In the following example, Table 2 and Figure 4, we assume that the SGR0 and λ values are equal to the assumptions .Figure 4 shows variation of SGR with the logarithm of tumour volume according to the Table 2. The estimated SGRThe authors declare that they have no competing interests.EM and PB initiated the study. EM developed the model and analyzed the data. EM, EFA, PB and RH drafted the manuscript. RH, VJ and LK participated in selecting images and delineating tumorus. All authors read and approved the final manuscript.


Respiratory variations in pulse pressure (PPV) during mechanical ventilation predict fluid responsiveness when the tidal volume is >8 ml/kg . The eff2O were included. Fluid challenges of 250 ml colloid were administered at the discretion of the anesthesiologist. PPV, hemodynamic variables, Paw and stroke volume (SV) measured by oesophageal Doppler were recorded before and after fluid challenges. Responders were defined by an increase in SV >15%.Twenty-five patients scheduled for open abdominal surgery with volume controlled ventilation 8 ml/kg, I:E ratio 1:2 and PEEP 5 cmHr = 0.91, P < 0.001) % to 6.0 (4.4 to 9.8)% , whereas Paw and SV were unchanged. Before fluid challenge, Paw was significantly correlated with PPV (In this study on patients undergoing open abdominal surgery ventilated with 8 ml/kg, specificity of PPV was low. Paw and PPV were strongly correlated and false positive PPVs were associated with high Paw. This finding indicates that not only tidal volume, but also airway pressures may affect the ability of PPV to predict fluid responsiveness.


During the past few decades, cancer therapy was based on the classical options of surgery, radiation and chemotherapy. And although there are examples where these techniques are applied with great success, there is still a lack of good treatment options for the most common types of cancer, especially in advanced cases with distant organ metastasis.During the last 20 years, basic research has considerably expanded our understanding of tumour biology. It has become obvious that cancer development and progression consists of several consecutive steps, and many molecular key events have been identified. One of the most important changes in our view of cancer in general was that we noticed the importance of tumour–host interactions. There is a constant cross-talk between tumour cells on one side and the surrounding stroma and immune cells on the other side. This is most obvious for tumour angiogenesis, but there are several other examples like the contribution of fibroblasts to the proteolytic capacity of the tumour or the various immune escape mechanisms used by the neoplastic cells to circumvent attack by the immune system.in vitro and animal experiments, indicating that specific disturbances in tumour–host interactions might slow down the progression of malignant disease. Therefore, it is challenging for everyone working in the field of oncology to keep up with the newest developments of anticancer strategies.Currently, several new approaches based on these discoveries are trying to make the step from laboratory to clinic. Many promising results were obtained from ‘Cancer Therapy-Molecular Targets in Tumour-Host Interactions’ provides in 16 chapters examples of molecular key events and mechanisms during tumour progression, which might be targeted to interfere with malignant progression. Special emphasis is put on antiangiogenesis to prevent the formation of new blood vessels, leading to reduced tumour growth due to a lack of oxygen and nutrients. Most articles cite the literature until 2004, which is sufficient to cover newer developments.Our main criticism concerning this book is that the reader does not really get an overview of the field. The preface by Georg F Weber is written well and leads into the field, but it is too short to really connect the following parts. The single chapters, all written by different authors, focus on very specialised topics, but largely fail to cover the broader field.There is no common format, and some chapters resemble more lab protocols. The length of the different articles varies considerably between 10 and 50 pages, and at least to us it is not obvious on which criteria the different aspects of the field were weighted. One of the major shortcomings is the far too low number of figures. These could have been used to facilitate reading and understanding of the topics, especially for readers not working in the particular fields.In summary, this book contains some interesting articles addressing specialised fields of research, and therefore it might be useful to readers searching for distinct topics. But we cannot recommend it for readers who want to get an overview over the field. The approach is not systematic enough and the single chapters focus too much on certain aspects, not covering the whole field in review style. Therefore, this book appears to be suitable only to a specialised audience.


Helical tomotherapy is a new form of image-guided radiation therapy that combines features of a linear accelerator and a helical computed tomography (CT) scanner. Megavoltage CT (MVCT) data allow the verification and correction of patient setup on the couch by comparison and image registration with the kilovoltage CT multi-slice images used for treatment planning. An 84-year-old male patient with Stage III bulky non-small cell lung cancer was treated on a Hi-ART II tomotherapy unit. Daily MVCT imaging was useful for setup corrections and signaled the need to adapt the delivery plan when the patient’s anatomy changed significantly. The spatients ,10. Kupeapy unit . In thisAn 84-year-old male patient presented with symptomatic left upper lobe and hilar mass, Stage III bulky non-small cell lung cancer without atelectasis. A kilovoltage CT  image  was takeSubsequent follow-ups after four and eight months showed  moderate radiation pneumonitis (Grade 2) that resolved with fibrosis. The patient follow up continued for 11 months with no evidence of cancer recurrence.3 in Plan 1 to 386 cm3 in Plan 2 and to 193 cm3 in Plan 3. The calculated mean lung dose was 16.3 Gy according to Plan 1, 10.4 Gy in Plan 2, and 7.9 Gy in Plan 3. The planned dose distribution according to Plan 1 is shown in Sensitive structures tolerance dose criteria  were metIn this case, there were at least three phases in tumour reduction, with initial phase of ca. 10 fractions (or 20 Gy with delivery of 2 Gy per fraction) when tumour reduction of 1.6% per day was noted. After this dose there was a rather rapid reduction in tumour size, of more than 5% per day which continued for three weeks until 40 Gy was administered. Finally, there was a slow reduction in tumour volume at 0.5% per day which probably continued when the treatment was finished at 60 Gy. The possible mechanisms for such a three phase reduction include an initial accumulation of radiation damage in Phase 1 before a radiosensitive Phase 2 of rapid reduction due to re-oxygenation occurs, while in Phase 3 cell death is counterbalanced by repopulation. Such a hypothesis requires verification in larger number of patients and correlation with histology or non-invasive information about tumour metabolism by PET/SPECT.The combined usage of kVCT and MVCT studies allowed high quality kVCT images for precise radiation dose calculations on tomotherapy planning station for both initial and adapted plans, while MVCT scans were used for accurate patient setup and monitoring of tumour evolution. MVCT has sufficient image quality for verification of daily treatment delivery allowing for plan adaptation according to tumour response. It can be used to quantitatively measure tumour response during radiotherapy. Furthermore, daily imaging provides data necessary for an optimal choice of GTV to PTV margin based on values for setup corrections and tumour dynamics.


This tumour is considered a grade I tumour by the World Health Organization.Spindle cell oncocytoma of the adenohypophysis is a rare tumour recently reported by Roncaroli We describe what is, to the best of our knowledge, the 14th case of its kind in the literature. A 45-year-old African woman presented clinical and radiological findings related to a nonfunctioning pituitary adenoma. The diagnosis was made on the basis of histological and immunohistochemical findings.The purpose of this work is to report a rare pituitary tumour and to describe its histological and immunohistochemical features, which were characterized by the expression of thyroid transcription factor 1 antigen by tumour cells. This fact could support the theory of a possible common origin of these tumours in pituicytomas. In fact, thyroid transcription factor 1 is considered to be a specific marker of pituicytes. WHO Classification of Brain Tumours and considered a WHO grade I tumour [et al. in 2002 [Spindle cell oncocytoma (SCO) of the pituitary gland is a recently described entity which was recognized by the 2007 I tumour . It was We report the case of a 45-year-old African woman without a particular medical history who presented with intermittent decrease of visual acuity and headache. Cranial magnetic resonance imaging (MRI) revealed a solid adenohypophysis mass of 2 × 1.5 × 1 cm with suprasellar extension but no invasive growth. This mass showed contrast enhancing in T1-weighted MRI scans (Figure Microscopic findings consisted of a solid spindle cell neoplasm with increased cellularity. Tumour cells were spindled to epithelioids organized in interlacing fascicles. The tumour cells had eosinophilic and oncocytic cytoplasm Figure . NuclearAn immunohistochemical study showed that most tumour cells expressed S-100 protein Figure . VimentiSCO is a rare tumour, with only 14 cases reported in the English-language literature (Table The radiological findings are nonspecific and do not differentiate these tumours from pituitary adenomas. In our case, they consisted of an enhanced mass of the sellar region.Histological examination is the only means of diagnosis -4. This et al. [These histological, immunohistochemical and fine structural features lead most authors to postulate a possible derivation of these tumours from folliculostellate cells. Very little is known about the functioning of the folliculostellate cells. Some authors have reported that these cells are implicated in long-distance communication in the anterior pituitary gland -8. Theseet al.  describeet al. .The diagnosis of these tumours may be challenging. In fact, they should be distinguished from meningioma in its oncocytic variant, granular cell tumour, pituicytoma, oncocytic neoplasm arising from developmental salivary gland remnants and oncocytic variant of a pituitary adenoma -4. RarelSCOs of the pituitary gland are rare tumours whose pathogenesis and management remain debated because of the few numbers of reported cases. These tumours are considered to have a good prognosis despite the early recurrences reported in some cases ,9. AdditThe authors declare that they have no competing interests.Written, informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.MM conceived of, coordinated with other coauthors and drafted and revised the manuscript. HH, IC, IBS, SH, HJ, MZ and NK participated by acquisition and analysis of literature data and helped to draft the manuscript. All authors read and approved the final manuscript.


We sought to determine the preclinical benefit of combining a Notch inhibitor (γ-secretase inhibitor (GSI)) and trastuzumab in both trastuzumab-sensitive and trastuzumab-resistant, ErbB-2-positive, BT474 breast tumours in vivo. We also studied if the combination therapy of lapatinib plus GSI can induce tumour regression of ErbB-2-positive breast cancer.We reported that Notch-1, a potent breast oncogene, is activated in response to trastuzumab and contributes to trastuzumab resistance in vivo.We generated orthotopic breast tumour xenografts from trastuzumab- or lapatinib-sensitive and trastuzumab-resistant BT474 cells. We investigated the antitumour activities of two distinct GSIs, LY 411 575 and MRK-003, Our findings showed that combining trastuzumab plus a GSI completely prevented (MRK-003 GSI) or significantly reduced (LY 411 575 GSI) breast tumour recurrence post-trastuzumab treatment in sensitive tumours. Moreover, combining lapatinib plus MRK-003 GSI showed significant reduction of tumour growth. Furthermore, a GSI partially reversed trastuzumab resistance in resistant tumours.Our data suggest that a combined inhibition of Notch and ErbB-2 signalling pathways could decrease recurrence rates for ErbB-2-positive breast tumours and may be beneficial in the treatment of recurrent trastuzumab-resistant disease. The Erbamoxifen  or aromaTrastuzumab is a humanised monoclonal antibody that binds the extracellular, juxtamembrane domain of ErbB-2 . The besEC) and a transmembrane Notch (NTM) . This final step can be pharmacologically inhibited by γ-secretase inhibitors (GSIs), which prevent the release of NIC, thus inhibiting Notch-mediated transcription and cell growth. The GSIs are currently in clinical trials for the treatment of breast cancer and other solid tumours  followed by implantation of a 17β-estradiol-containing silastic capsule of 0.3 cm in length with a constant release providing 83–100 pg ml−1 as described previously , trastuzumab  or lapatinib , LY 411 575 GSI  or MRK-003 , or trastuzumab plus MRK-003 or LY 411 575 GSI or lapatinib plus MRK-003 GSI. Tumour area (l × w) was measured weekly using Vernier calipers and cross-sectional area ((l × w)Π)/4) was calculated and graphed. Tumour recurrence was monitored and tumour area measured after treatments with trastuzumab or trastuzumab plus GSI were ceased at the time tumours were no longer detectable by the Vevo 770 Ultrasound Imaging system . Tumour recurrence post treatment was monitored up to ∼100 days. Protocols that were used to study breast tumour xenografts in mice were approved by Loyola University's Institutional Animal Care and Use Committee.BT474 cells were purchased from the American Tissue Cell Culture  and maintained as described previously (μm) were sliced from formalin-fixed, paraffin-embedded tumour samples, followed by antigen retrieval to unmask the epitope. Immunohistochemical staining was performed as described previously (y axis was determined by taking an average number of Ki67-positive cells from 60 high-power fields (HPFs) at × 40 magnification per treatment group. Haematoxylin and eosin (H/E) was performed to ensure the presence of tumour cells in the tumour sections.Tumour sections  assay with the TMR detection kit  was used to detect 3′OH-associated DNA fragmentation resulting from apoptosis. Paraffin-embedded BT474 trastuzumab- and lapatinib-sensitive tumours extracted from xenografts as described above were examined for the presence of TUNEL-positive cells from each treatment group according to the manufacturer's instructions. The TUNEL assay was performed using 3–5 tumours from each treatment group. The number of TUNEL-positive cells shown on the M HEPES, 1% Triton X-100, 150 mM NaCl, 5 mM EDTA, 10 μg ml−1 pepstatin A, 10 μg ml−1 leupeptin, 10 μg ml−1 aprotinin, 25 μg ml−1 PMSF, 10 μg ml−1 TLCK, 10 μg ml−1 TPCK, 1 mM o-vanadate, and 10 mM NaF). The lysate was sonicated, followed by centrifugation at 10 000 g for 5 min. The supernatant was collected and protein concentration was measured using the BCA protein assay . Tumour lysates were then subjected to SDS–PAGE and western blotting  and Deltex1 . The expression level of 18S  was used as a loading control. The PCR was performed as previously described  according to the manufacturer's instructions. Total RNA was reverse transcribed to total cDNA using the TaqMan reverse transcription Kit  according to the manufacturer's instructions. Real-time PCR was performed using cDNA as template to detect relative expression levels of Notch targets such as in vivo study. Based on experience, we hypothesised the following average tumour size for the four groups in trastuzumab- or lapatinib-sensitive xenograft studies at the end of the experiment : 1 vehicle=2.0 (s.d.=0.3); 2 trastuzumab or lapatinib=0.4 (s.d.=0.1); 3 GSI=1.5 (s.d.=0.1); and 4 GSI+trastuzumab or lapatinib <0.1 (s.d.=0.01). For the trastuzumab-resistant xenograft study, the average tumour size for vehicle, GSI, and GSI+trastuzumab should remain the same as above. However, as these are trastuzumab-resistant tumours, we would expect the average tumour size for the trastuzumab group as 1.5 cm2. Calculations were conducted using PASS 2002 software . In a one-way ANOVA, same sample sizes of 7 were obtained for all the four groups whose means are to be compared, assuming 100% tumour take. The total sample of 28 mice achieves 95% power to detect differences among the means vs the alternative of equal means using an F-test at a significance level of 0.05. The common s.d. within a group is assumed to be between 1 and 0.01. However, experience suggests that tumour take will be 50–70% therefore, in order to maximise the likelihood that 7 subjects per group will present with tumours, we must assume that a sample of 7 represents 50–70% from a group of 14 mice, for a total of 56 mice per experiment of four groups. Each mouse was identifiable with a numbered tag. Each tumour area on the left flank and right flank of the mouse was measured weekly with Vernier calipers. At the end of the study, tumour CRA was calculated and linear regression analysis was performed to determine the slope of the line for determination of the rate of growth for each tumour. Slopes of lines were used only if the correlation coefficients were ⩾0.85. A one-way ANOVA with Bonferroni correction for multiple comparisons and α=0.05 was used to test statistical significance between groups for tumour growth rates, mRNA expression levels, and IHC assays. A nonpaired Student's t-test was used to test statistical significance between two groups.Karyn Richlyk, a statistician at Loyola University Medical Center, assisted in determining the number of mice needed for the in vitro studies . Lapatinib plus MRK-003 GSI were not as effective as trastuzumab plus MRK-003 GSI in inhibiting tumour growth of BT474 xenografts. A combination of MRK-003 GSI plus trastuzumab was sufficient to prevent tumour recurrence, whereas a combination of LY 411 575 plus trastuzumab was only able to reduce tumour recurrence. The observed differences in efficacy between MRK-003 and LY 411 575 GSI was also observed by recent data from in vitro, whereas the effect of LY 411 575 was reversible after drug washout. These results, in addition to data from the current paper, suggest that the best combination strategy for a future clinical trial to prevent tumour recurrence of ErbB-2-positive breast cancer could be trastuzumab plus MRK-003 GSI.We investigated the therapeutic benefits of two distinct inhibitors to block ErbB-2 (trastuzumab or lapatinib) and Notch (MRK-003 or LY 411 575 GSI) pathways. Although lapatinib is a more potent inhibitor of ErbB-2 activity In conclusion, our findings suggest for the first time that the benefit of using a combination of trastuzumab plus a GSI is prevention of ErbB-2-positive breast tumour recurrence. Because Notch is a breast oncogene that is critical for survival and proliferation of breast cancer cells, our findings strongly suggest that combined treatment with a Notch inhibitor should be an effective therapeutic strategy to prevent tumour recurrence and possibly disease progression and death in ErbB-2-positive breast cancer. Our data also suggest that a combination of trastuzumab plus MRK-003 GSI could benefit women with recurrent, or possibly resistant, ErbB-2-positive breast cancer to prevent disease progression.