The neuromodulators serotonin, acetylcholine, and dopamine have been proposed to play important roles in the execution of movement, control of several forms of attentional behavior, and reinforcement learning. While the response pattern of midbrain dopaminergic neurons and its specific role in reinforcement learning have been revealed, the roles of the other neuromodulators remain elusive. Reportedly, neurons in the dorsal raphe nucleus, one major source of serotonin, continually track the state of expectation of future rewards by showing a correlated response to the start of a behavioral task, reward cue presentation, and reward delivery. Here, we show that neurons in the pedunculopontine tegmental nucleus (PPTN), one major source of acetylcholine, showed similar encoding of the expectation of future rewards by a systematic increase or decrease in tonic activity. We recorded and analyzed PPTN neuronal activity in monkeys during a reward conditioned visually guided saccade task. The firing patterns of many PPTN neurons were tonically increased or decreased throughout the task period. The tonic activity pattern of neurons was correlated with their encoding of the predicted reward value; neurons exhibiting an increase or decrease in tonic activity showed higher or lower activity in the large reward-predicted trials, respectively. Tonic activity and reward-related modulation ended around the time of reward delivery. Additionally, some tonic changes in activity started prior to the appearance of the initial stimulus, and were related to the anticipatory fixational behavior. A partially overlapping population of neurons showed both the initial anticipatory response and subsequent predicted reward value-dependent activity modulation by their systematic increase or decrease of tonic activity. These bi-directional reward- and anticipatory behavior-related modulation patterns are suitable for the presumed role of the PPTN in reward processing and motivational control. The pedunculopontine tegmental nucleus (PPTN) is the major source of cholinergic projections in the midbrain, but also contains glutamatergic, gamma aminobutyric acid (GABA)ergic, dopaminergic, and noradrenergic neurons . The PPTMany previous studies, including ours, reported the phasic activity of PPTN neurons in response to reward, sensory stimulus, and movement . Some stRecent neurophysiological studies of the serotonergic dorsal raphe nucleus (DRN) reported that DRN neurons showed either an increase or decrease in tonic activity to reward-related cues and reward outcomes , and theTo investigate the relationship between task-related tonic activity and reward-related modulation, we analyzed PPTN neuronal activity during several phases of a behavioral task, i.e., just before the start of the task, just after the start of the task, at reward cue presentation, and at reward delivery. In addition to the neurons we reported previously that exhibited an increase in tonic activity, other PPTN neurons showed a decrease in tonic activity during the behavioral task, similar to the activity of some DRN neurons. We found a correlation between the tonic increase or decrease in activity to the start of the task and the responses to large/small reward cues, but not to the delivery of large/small rewards. Furthermore, a partially overlapping population of neurons showed preparatory activity modulation that depended on the anticipatory fixational behavior of the monkeys. This result suggests that PPTN neurons encode both the externally cued reward value and internal anticipatory state signals by systematic changes in their tonic firing rate, both in excitatory and suppressive directions.Macaca fuscata; animal Ds, male; animal Tm, female; animal Dn, male) while they performed a reward-biased visually guided saccade task. All experimental procedures were performed in accordance with the National Institutes of Health Guidelines for the Care and Use of Laboratory Animals and approved by the Committee for Animal Experiments at Okazaki National Research Institutes and Osaka University.We recorded neuronal activity from the PPTN in three Japanese macaque monkeys . The monkeys initially fixated on the central target, then made a saccade to the peripheral target, and finally received a juice reward. During the initial fixation period, the shape of the FT cued the animals to expect either a large or small reward upon the successful completion of the trial. In the recordings from animal Ds, an uninformative small fixation point (FP) was presented initially at the center of the screen. The monkey was required to fixate on the FP within 3000 ms to a precision of ± 2°. After 400–800 ms fixation, the FP was replaced by a square or triangle FT, which was associated with the reward magnitude. In the recordings from animals Tm and Dn, the initial stimulus was a square or circle FT, and its shape was associated with large or small rewards, respectively. The FT shape-reward magnitude contingency was switched at quasi-random intervals .The animals performed a reward-biased visually guided saccade task. This task was comparable to those used in recordings from basal ganglia nuclei and dopaminergic neurons in which the shape of the fixation target  indicated the reward magnitude , a saccade target  appeared at an eccentricity of 10° from the FT in 1 of 2 (left or right) or 8  possible directions. The monkey was required to saccade to the ST within 80–500 ms to a precision of ±2°. Successful trials were rewarded with juice presented together with a tone at 100 or 300 ms after the ST disappeared. The large and small rewards consisted of 3 or 1 drops of juice (each drop ~0.1 ml), respectively. If the animal broke fixation at any time during the fixation period or failed to make a saccade to the ST, an error tone sounded and the trial was aborted. The intertrial interval, which started at the time of reward offset and lasted until the onset of the initial stimulus in the next trial, was fixed at 1500 ms in the recordings from animal Ds, and quasi-randomly varied (within 1.5–2 s) in the recordings from animals Tm and Dn.Guide tubes held within the recording chamber were aimed at the PPTN of the monkeys using magnetic resonance imaging (2.2 T) under general anesthesia. The locations of the recorded neurons were reconstructed for two monkeys from the readings of the micromanipulator and those of the guide grids of the recording chamber, referenced to a single marker site selected for each monkey . CorrectWhile the PPTN is the major source of cholinergic projections in the brainstem , it alsoOur database consisted of 507 neurons in animal Ds (saccade task with FP presentation), 156 neurons in animal Tm, and 29 neurons in animal Dn. The data from monkeys Tm and Dn are from the same neurons recorded in a previous study . The anaWe used receiver operating characteristic (ROC) analysis to compare the firing rates in two time windows during a trial or for two different task conditions. In principle, ROC analysis evaluates the reliability by which an ideal observer could correctly distinguish between 2 conditions from the neuronal signal. The ROC value is calculated as the probability that a randomly chosen firing rate from the first condition has a higher value than a randomly chosen firing rate from the second condition , the normalized activity of each neuron was calculated as the ROC value comparing the firing rate of the neuron collected in a 200 ms window centered on that time versus the firing rate collected during a pre-fixation period represented by a 600 ms window before the onset of the initial stimulus to display neuronal activity during both the task period and intertrial interval. Neurons were classified as “tonic excitatory” or “tonic suppressive” based on their significant increase or decrease in activity during the post-fixation period  versus their activity in the pre-fixation period . We defined the fixation period response as the ROC value comparing the firing rate in the same 600 ms time window. An ROC value >0.5 implies that neuronal activity is increased after the onset of the initial stimulus.For the analysis of task-related tonic changes in activity , the normalized activity of each neuron was calculated as an ROC value separately for the large and small reward trials. We calculated reward-related modulation by comparing the firing rate in the large versus small reward trials, separately for the reward cue period (0–600 ms after FT onset) and outcome period (0–600 ms after reward delivery), using the Wilcoxon rank-sum test (p < 0.05) and ROC analysis. An ROC value >0.5 implies that neuronal activity is higher in the large reward condition (positive reward modulation). We also determined the contributions of the predicted reward magnitude and FT shape to the neuronal responses. Multiple linear regression analysis was performed in which the responses were modeled by a linear sum of the predicted reward magnitude and FT shape. From the regression coefficients of the model, we confirmed that the neuronal activity was significantly modulated by the predicted reward magnitude , we used the reaction time to fixate on the initial target (RTit) as a measure of the monkeys’ anticipation of the occurrence of an upcoming event. Even before the appearance of the initial stimulus, our monkeys frequently shifted their gaze to the center of the screen (entered a 3° window), i.e., they performed self-initiated movements based on their anticipation of an upcoming visual event. An RTit <0 implies that the monkey made an anticipatory gaze shift before the appearance of the initial target, while an RTit >0 implies that the monkey made a gaze shift after the appearance of the target. We classified the trials into short and long RTit categories , and the normalized activity of each neuron was calculated as an ROC value separately for the short and long RTit trials. We calculated behavior-related modulation by comparing the firing rate in the short versus long RTit trials for the pre-fixation period  using the Wilcoxon rank-sum test (p < 0.05) and ROC analysis. An ROC value >0.5 implies that neuronal activity is higher in the short RTit condition .For the analysis of anticipatory behavior-related modulation .The electrophysiological properties of neurons were quantified, such as spike duration, spiking irregularity, and firing rate. Spike duration was measured between the first negative deflection and the peak of the second positive deflection of the spike waveform. Spiking irregularity was measured for each spike using the coefficient of variation (CV) of five successive interspike intervals (ISI), where the standard deviation (S.D.) of the ISI was divided by the mean of the ISI (CV = S.D. (ISI)/mean (ISI)). The irregularity index of each neuron was defined as the median of the CV of all of its spikes recorded during the performance of correct trials. The firing rates of tonic excitatory and suppressive neurons during the pre- and post-fixation periods were compared using the Wilcoxon rank-sum test . During fixation on the reward-conditioned FT, the monkeys could expect either a large or small reward upon the successful completion of the trial depending on the shape of the FT. Animal behavior is influenced by the predicted reward magnitude, such that there is a higher success rate and shorter saccadic reaction time to the ST in large reward-predicted trials than in those with a small reward . This tonic activity and differential response ended around the time of reward delivery, and the neuronal activity was almost unrelated to the actual magnitude of the given reward , and some of these neurons show predicted reward-related activity modulation . Figure n reward . Thus, tFigure 2B illustrates an example neuron that decreased its tonic activity during the task period. Its decrease in activity started before the appearance of the FP, and then showed lower activity to a large reward-indicating FT (negative reward modulation). This differential response faded away during the saccade period and its activity returned to the pre-fixation level after reward delivery. There was no significant difference in activity according to the magnitude of the given reward. Thus, opposite to the tonic excitatory neurons, this neuron might encode the expectation of future rewards by decreasing its activity. Some tonic suppressive neurons additionally responded to multiple task events, such as the appearance of the visual stimulus and saccade, similar to the tonic excitatory neurons , regardless of whether the initial target was an uninformative FP  or a reward-conditioned FT . Furthermore, another group of PPTN neurons showed a reverse response pattern; their activity was tonically decreased around the time of the initial target appearance and rebounded at the end of the task . Similarly, many tonic suppressive neurons also started to decrease their activity before the appearance of the initial target . These preparatory changes in activity were slightly more frequent in tonic excitatory neurons than in tonic suppressive neurons . Thus, the tonic activity was triggered not only by the appearance of the external visual stimulus but also by the anticipation of the upcoming event and/or motivation of the monkeys. We will discuss the relationship between the preparatory changes in activity and the monkeys’ anticipatory behavior in detail in a later section.Tonic excitatory and suppressive neurons started to change their tonic activity even before the appearance of the initial target, both in the fixed and quasi-randomized intertrial interval conditions. We first compared the time course of this anticipatory modulation for tonic excitatory and suppressive neurons. The start of the changes in neuronal activity was defined as the time at which the normalized activity exceeded that of the pre-fixation period by more (or less) than two standard deviations. Many tonic excitatory neurons showed an increase in activity before the appearance of the initial target . However, when comparing the firing rate during the active period (post-fixation period of the tonic excitatory neurons and pre-fixation period of the tonic suppressive neurons) and silent period (pre-fixation period of the tonic excitatory neurons and post-fixation period of the tonic suppressive neurons), there was no significant difference . Therefore, we concluded that these two groups of neurons showed a similar range of firing rates. In addition, tonic excitatory and suppressive neurons did not show a significant difference in spike duration , spiking irregularity , and recording site . Therefore, if the tonic activity reflected the monkeys’ expectation of future rewards, then the tonic excitatory neurons should exhibit stronger activity to large reward cues . Thus, the tonic suppressive neurons should exhibit weaker activity to large reward cues . Conversely, if the tonic changes in activity were independent of the expectation of the reward value and encoded some variables about the behavioral task, there would be no systematic relationship between the sign of tonic activity changes and reward-related activity modulation.Figure 2A, some tonic excitatory neurons exhibited higher activity in response to the large reward-indicating FT than the small reward-indicating FT. This positive reward coding was the major pattern of the predicted reward-related modulation of the tonic excitatory neurons. The population average normalized activity is shown in Figure 5A for neurons that showed an increase in tonic activity and positive reward modulation for the reward-conditioned FT . The data from 2 reward tasks were pooled and presented together because they showed similar results. At the population level, activity modulation started even before the appearance of the initial target. If the large reward cue appeared, the higher activity was maintained, whereas if the small reward cue appeared, the activity decreased, but was still higher than the activity during the intertrial interval. Consistent with our previous finding, this differential response to the reward cue was dependent on the predicted reward magnitude rather than the shape of the FT , indicating that the tonic activity encoded the magnitude of the predicted reward rather than a simple visual response to the target stimulus (N = 17/74). A small population of tonic excitatory neurons (N = 16/372) showed a weak negative reward modulation, in that their response was smaller for the large-reward indicating cue.As shown in stimulus . In a suN = 14/110, Figure 5B). Opposite to the population activity pattern of the tonic excitatory neurons, the tonic suppressive neurons keep silent during the presentation of a large reward cue, whereas if a small reward cue appeared, their activity increased, but it was still lower than their activity during the intertrial interval. Similar to the tonic excitatory neurons, the differential response to the reward cue was dependent on the predicted reward magnitude rather than the shape of the FT . Some neurons maintained negative reward modulation until shortly after reward delivery (N = 6/14), and only two tonic suppressive neurons showed positive reward modulation to the FT.Tonic suppressive neurons also showed a correlation between their task-related tonic activity and reward-related modulation. Some tonic suppressive neurons showed negative reward modulation to the FT , but not after reward delivery . This result further supported the view that PPTN neurons encoded the prediction of future rewards by their bi-directional changes in tonic activity, but did not primarily encode the actual reward value information. These tonic firing PPTN neurons might play a role in the reward prediction-based behavioral control system rather than the actual reward-based feedback valuation system.We then analyzed the correlation between the strength of tonic activity modulation during the task execution period and the differential response to the reward cue and reward delivery in order to examine the pattern of reward value coding in PPTN neurons. We used ROC analysis to measure the strength of tonic activity modulation and reward-related response of each neuron . We founr = 0.02, p = 0.34), possibly because there was a substantial number of neurons that showed strong tonic changes in activity during the task period, but had no reward-related modulation. Overall, we found no relationship between the absolute strength of the tonic activity during the task and the absolute strength of the reward-related modulation; however, the sign of the reward-related modulation could be predicted by the increase or decrease in tonic activity.Then, we examined the relationship between the absolute strength of tonic activity modulation during the task execution period and the absolute strength of the reward-related modulation after FT presentation. We used the absolute value of the difference between the ROC value and 0.5. The absolute ROC value for tonic activity modulation was not correlated with the absolute ROC value for reward-related modulation  and appearance of the FP . This neuron showed a predictive increase in activity before FP appearance, and this tonic activity persisted during the task period. The start of the changes in neuronal activity was time locked to the gaze shift to the center of the screen , rather than the appearance of the FP . In other words, the neuron showed higher anticipatory activity in the short RTit trials than in the long RTit trials . Activity reached a plateau shortly after the anticipatory gaze shift, even before the appearance of the FP. After the reward-conditioned FT was presented during fixation, this neuron also showed higher activity in response to the large reward-indicating FT than the small reward-indicating FT (positive reward modulation).The anticipatory response was correlated to the monkeys’ anticipatory behavior. Figures D shows a neuron that decreased its tonic activity during the task period. Similar to the tonic excitatory neuron shown in Figures B, the pause in its activity was started at the time of the centering gaze shift . Therefore, this neuron showed higher anticipatory activity in the long RTit trials than in the short RTit trials , and this differential response was only apparent in the pre-fixation period .Similarly, tonic suppressive neurons showed a predictive decrease in activity before the appearance of the initial stimulus in an RTit-dependent manner. Figure 7A for neurons that showed an increase in tonic activity and positive behavioral modulation. If the monkeys made a short RTit for a centering gaze shift, a subset of tonic excitatory neurons showed higher activity during the pre-fixation period and this activity reached a plateau before the appearance of the FP, whereas if the monkeys made a long RTit for a centering gaze shift, there was a slower increase in activity . There was a small population of tonic excitatory neurons (N = 10) that showed a weak negative behavioral modulation in that their response was smaller in the shorter RTit trials. Opposite to the tonic excitatory neurons, some tonic suppressive neurons showed higher activity during the pre-fixation period in the short RTit trials than in the long RTit trials , and only seven neurons showed positive behavioral modulation. Thus, the increase or decrease in tonic activity reflected the motivational and/or attentional state of the monkey based on the anticipation of an upcoming event.We found correlations between the tonic activity modulation and anticipatory behavior-related modulation. The population average normalized activity is shown in r = 0.40, p < 0.001, Figure 7C). Furthermore, the absolute strength of the anticipatory response could be predicted by the tonic activity modulation during the task. The absolute ROC value for the tonic activity modulation was positively correlated with the absolute ROC value for the anticipatory response . Thus, the sign and strength of the anticipatory behavior-related modulation could be predicted by the increase or decrease in tonic activity. Neurons that had behavioral dependency basically showed a predictive change in their firing rate. We also analyzed the effect of reward history on the monkeys’ behavior and neuronal activity, but there was no significant correlation.We then analyzed the correlation between the strength of tonic activity modulation and anticipatory behavior-related modulation. We found that the strength of tonic activity modulation during the task execution period was positively correlated with anticipatory behavior-related modulation  and anticipatory behavior-related modulation . We then questioned whether PPTN neurons encoded the externally cued predicted reward value and internal anticipatory state by a correlated increase or decrease in their tonic neuronal activity. The example neuron in Figure 6B showed correlated encoding such that the neuron initially showed behavior-related anticipatory increases in activity and then showed a predicted reward-related differential response. Figure 8 shows the correlation between the strength of reward-related modulation and behavior-related modulation. Some neurons showed both predicted reward value-related activity modulation and anticipatory behavior-related activity modulation . In addition, by correlation analysis, we found that the predicted reward-related modulation after FT presentation was positively correlated with anticipatory behavior-related modulation before the appearance of the initial stimulus . On the other hand, largely separate groups of neurons showed either predicted reward value-related activity modulation  or anticipatory behavior-related activity modulation . Thus, the prediction of the reward-value signal and anticipatory behavior-related signal converged in a subset of PPTN neurons, while other separate populations of neurons carried these two signals independently.Thus far, we have described separately the correlation between the tonic activity modulation during the task and predicted reward value-related modulation  to identify the neurotransmitter of the recorded neuron. Additionally, we found that the tonic activity pattern of our recorded PPTN neurons had no clear relationship with several electrophysiological properties. One future direction is to determine their neuronal activity and neurotransmitter content by using new techniques .In addition to the tonic excitatory neurons and their positive reward- and behavioral-modulation we reported previously , here, wThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Differential lung ventilation (DLV) is used to salvage ventilatory support in severe unilateral lung disease in the critical care setting. However, DLV with a double-lumen tube is associated with serious complications such as tube displacement during ventilatory management. Thus, long-term ventilatory management with this method may be associated with high risk of respiratory incidents in the critical care setting.We devised a novel DLV technique using two single-lumen tubes and applied it to five patients, two with severe unilateral pneumonia and three with thoracic trauma, in a critical care setting. In this novel technique, we perform the usual tracheotomy and insert two single-lumen tubes under bronchoscopic guidance into the main bronchus of each lung. We tie the two single-lumen tubes together and suture them directly to the skin. The described technique was successfully performed in all five patients. Pulmonary oxygenation improved rapidly after DLV induction in all cases, and the three patients with thoracic trauma were managed by DLV without undergoing surgery. Tube displacement was not observed during DLV management. No airway complications occured in either the acute or late phase regardless of the length of DLV management (range 2-23 days).This novel DLV technique appears to be efficacious and safe in the critical care setting. Differential lung ventilation (DLV) was reported for the first time in 1931 as a technique for use in thoracic anesthesia ,3. The iA novel DLV technique was applied to five patients with severe hypoxemia refractory to conventional ventilation and application of positive end-expiratory pressure. Two patients had severe unilateral pneumonia, and the other three patients suffered thoracic trauma: one with unilateral pneumothorax and massive air leakage, one with massive hemoptysis due to pulmonary contusion, and one with tracheal rupture at the carina.This study followed the principles of the Declaration of Helsinki. The ethics committee at our institution does not require its approval or informed consent for retrospective studies such as this study.Technique  under bronchoscopic guidance into the main bronchus of the unaffected lung.3. We then extend the tracheotomy site using two blunt hooks to secure space for insertion of the second tube. We quickly but carefully insert a second single-lumen tube (7.0-mm ID) under bronchoscopic guidance into the main bronchus of the affected lung.4. We ascertain proper anatomical position of both tubes by bronchoscopy and chest X-ray.5. Finally, we tie the two single-lumen tubes together with silk suture and suture them directly to the skin.6. Differential ventilator settings using two ventilator circuits are applied to each lung asynchronously. As a rule, administration of neuromuscular blockade is not necessary.The demographic and clinical details of the five patients undergoing this novel DLV technique are shown in Table The described technique was successfully performed in all five patients. Complications such as tube displacement, tube obstruction, and tracheal or bronchial injury were not observed regardless of the length of DLV management (range 2-23 days). One patient with unilateral pneumonia died due to septic shock on day 2 of DLV. The four remaining patients were followed up after the end of DLV management, and none experienced complications of airway stenosis after DLV.Our DLV technique allowed successful ventilatory management of all five patients without complications. These results demonstrate that this novel technique may be effective for ventilatory support in critically ill patients requiring DLV management.Patient 5 presented with tension pneumopericardium, bilateral pneumothorax, and massive subcutaneous emphysema due to carinal laceration . OperatiAlthough the double-lumen tube of the conventional DLV technique is mainly used in the intensive care setting, serious complications such as tube displacement have been described . AccordiOur DLV technique has several advantages over the conventional DLV method using a double-lumen tube.1) It is difficult for tube displacement to occur with our method. In case of proximal displacement, it is difficult for bilateral ventilation to occur, unlike with the double-lumen tube, because the cuffs of the two single-lumen tubes prevent their movement above the carina. In case of distal displacement, unilateral ventilation will never occur, unlike with the double-lumen tube, because the distal end of each tube is located within a main bronchus. In addition, there is little influence from head movements because tube fixation is by direct suture at the tracheotomy site . A major2) Because the internal diameter of each tube used in our technique is larger than the individual tube diameters in the double-lumen tube, a regular bronchoscope and suction tubing can be used. In addition, risk of tube occlusion is reduced.3) The two cuffs used in our technique doubly isolate the relatively healthy lung from harmful contaminants in the contralateral diseased lung, whereas with the double-lumen tube, the diseased lung is isolated from the contralateral lung by only one cuff.4) Ours is the only technique to provide non-operative management of carinal laceration. The advantages of safety and efficacy offered by our DLV technique would be especially appreciated in the critical care setting rather than during surgical anesthesia because of the potentially long period of DLV use generally required in the critical care setting.Because the performance of tracheotomy is a burden for the patient, the use of our DLV technique should be limited to the rescue of the patients with life-threatening respiratory conditions.We acknowledge several limitations in this study. First, the design of this study was a case series, and there was no control. The influence of different pathophysiologic issues, such as severity of respiratory failure, lung pathology, and cause of admission to the intensive care unit, on the safety and efficacy of our DLV technique require further evaluation. Second, the sample size in this study was small, and the follow-up period was short. Although we experienced no technical difficulties in insertion of the two tubes or airway complications in either the acute or late phase, further study is required to evaluate the safety of this technique, especially in patients with a narrow trachea such as women and adolescents.Our novel DLV technique using two single-lumen tubes may have several advantages of safety and efficacy over the conventional double-lumen tube during the long period of DLV use in the critical care setting.The authors declare that they have no competing interests.KY participated in study design and in data collection and interpretation and drafted the manuscript. YN conceived the study and its design and helped to draft the manuscript. SF, YK, and TS participated in data interpretation. HO had a major impact on the interpretation of data and critical appraisal of the manuscript. All authors read and approved the final manuscript.


AbstractThis article provides an overview of research on chromatin diminution (CD) in copepods. The phenomenology, mechanisms and biological role of CD are discussed. A model of CD as an alternative means of regulating cell differentiation is presented. While the vast majority of eukaryotes inactivate genes that are no longer needed in development by heterochromatinization, copepods probably use CD for the same purpose. It is assumed that the copepods have exploited CD as a tool for adaptation to changing environmental conditions and as a mechanism for regulating the rate of evolutionary processes. Pseudocalanus Boeck, 1872 revealed a large number of Feulgen-positive matePageBreakrial (Chromatin diminution (CD) in Cyclopoidais the removal of part ofthe chromosomal material from cells of the somatic cells line in one or two sequential cleavage divisions, while germ-line cells retain their nuclear DNA unchanged throughout ontogeny . CD in fmaterial . This mamaterial .Cyclops furcifer Claus, 1857, Cyclops strenuus divulsus Lindberg, 1957, Cyclops strenuus strenuus Fisher, 1851 and Mesocyclops edax Forbes, 1891 during prophase of their first meiotic division and Cyclops kolensis  and are distributed throughout the eliminated genome  (Cyclops kolensis population (at least 25 million), the sequence data has been under strong selection to not change.The phenomenon of chromatin diminution (CD) has been discovered in 23 species of freshwater copepods . The timdivision . The numorg 1901 . These okolensis . Standifomosomes . Heterozfragment . The repd genome . The stuafter CD  Some seqafter CD . The invlls line . Compara(97–98%) . This meOf special interest is the research on genome endoreduplication in cyclops with CD  Preparation for the reduction of a major part of the genome, which involves lengthening of the prediminution interphase and the appearance of G-bands in chromosomes prior to diminution. The G-bands might be involved in reprogramming the functionally active part of the genome through the mechanisms of DNA methylation and histone modifications of somatic cells chromosomes before CD;PageBreak2) Activation of the sites of chromosomes breaks during interphase of the cell cycle when CD occurs. It is probable that the chromosomes breakage sites are localized in regions associated with the nuclear matrix;3) Cutting at chromosomes breakage sites. Immediately after cutting, the chromosome DNA strand is restored;4) Compacting of the excised DNA and formation of a pore-free membrane around it to produce granules;5) Degradation of the granules of excised DNA during 2–3 subsequent divisions.Thus, the CD process, presumably, involve many genes.Cyclopoidae species to have achiasmatic meiosis  has revealed that a large-scale rearrangement of the genome has arisen in this suborder withPageBreakout any visible morphological changes. Evolutionary events that have involved changes in genome size but not changes in chromosome number are evidenced by multiple genome size differences within the genera Mesocyclops Sars, 1913 and between populations of Thermocyclops crassus Fischer, 1853 (Cyclops strenuous strenuus like gonomery (Cyclops strenuous strenuus; and the presence and absence of CD for Russian and German populations of Cyclops insignis (Cyclops kolensis genome, the complex structure of its eliminated DNA, and the selective removal of some sequences, (Cyclopoida species that are distinguished by the occurrence or lack of CD, by peculiarities of the CD process and by other cytogenetic characteristics. The mechanism of cryptic speciation is not known yet, but it is likely that hybrids of cyclops with CD and without CD will fail as a result of a compromised ability to regulate CD. Disruption of the coordinated network of genes that control each of the above-proposed stages of CD will inevitably lead to the disturbance of the CD process and, as a result, to errors in the processes of development and differentiation of the organism that will most likely cause the death for the given organism. Consequently, the occurrence of CD in Cyclops evolution should automatically lead to the emergence of a new species. To confirm this hypothesis, it would be of interest to cross the German population of Cyclops insignis, whichhave CD and the Russian population of Cyclops insignis, in which CD absent.ulations , 2006c. ulations . Comparaer, 1853  (it’s prgonomery , the cytinsignis .The molequences,  suggestsCyclops species raises another side of the biological significance of CD (The detection of polyploid cells in some ce of CD . With thDNA sequences is offset by the necessity of replicating and maintaining multiple copies of much additional genetic material that will never be required in differentiated somatic cells. An alternative but more economical path to the same end is to eliminate unused DNA from the somatic cells line genome during CD and then to repeatedly amplify the genome of somatic cells.Based on the above reasoning we can make the following assumptions about biological role of CD:1. Chromatin diminution is an alternative form of regulation of cell differentiation during which there is a total loss of mostly redundant DNA, while in the vast majority of eukaryotes part of the genome is inactivated through heterochromatinization;2. CD coevolves with polyploidy to regulate gene dosage in somatic tissues;3. CD is a tool for adaptation to changing environmental conditions;4. CD is a mechanism for regulating the rate of evolutionary processes.PageBreakThus, even a brief acquaintance with the facts established recently permits a conclusion that the phenomenon of CD is a unique tool to study the eukaryotic nucleus organization and some questions of evolution.


Hypothesizing that members of families enriched for longevity delay morbidity compared to population controls and approximate the health-span of centenarians, we compared the health-spans of older generation subjects of the Long Life Family Study (LLFS) to controls without family history of longevity and to centenarians of the New England Centenarian Study (NECS) using Bayesian parametric survival analysis. We estimated hazard ratios, the ages at which specific percentiles of subjects had onsets of diseases, and the gain of years of disease-free survival in the different cohorts compared to referent controls. Compared to controls, LLFS subjects had lower hazards for cancer, cardiovascular disease, severe dementia, diabetes, hypertension, osteoporosis, and stroke. The age at which 20% of the LLFS siblings and probands had one or more age-related diseases was approximately 10 years later than NECS controls. While female NECS controls generally delayed the onset of age-related diseases compared with males controls, these gender differences became much less in the older generation of the LLFS and disappeared amongst the centenarians of the NECS. The analyses demonstrate extended health-span in the older subjects of the LLFS and suggest that this aging cohort provides an important resource to discover genetic and environmental factors that promote prolonged health-span in addition to longer life-span. The Long Life Family Study (LLFS) is an ongoing study of longevity and healthy aging in 583 families and almost 5000 family members demonstrating clustering for longevity. Median age of the probands and their siblings (the older generation or “generation one”) at enrollment was 92 years with an age range of 72–109 years. This substantial longevity was associated with decreased prevalence of age-related diseases such as diabetes and peripheral artery disease compared to subjects in the Framingham Heart Study and Cardiovascular Health Study , which scored the degree of familial longevity using sex and birth-year cohort survival probabilities of the proband and their siblings . EligibiIn both LLFS and NECS, socio-demographic, vital status, and medical history data were collected via mailed questionnaires or in-person visits. Medical history questionnaires in both studies asked similar questions. Next-of-kin assisted when necessary. Ages of onset for the following diseases were used for the analysis: cancer (excluding non-melanoma skin cancers), chronic obstructive pulmonary disease , cardiovascular disease , dementia, diabetes, hypertension, osteoporosis , Parkinson’s disease, or stroke. Because dementia was based on self- or proxy-reported medical history with possibly low sensitivity, a report of dementia should be considered as “severe dementia” rather than mild or moderate cognitive impairment. The selected diseases comprise the top 10 most prevalent diseases to afflict people age 65+ years according to the United States Centers for Disease Control (CDC) . In the Patients’ characteristics are displayed by median, range, and proportions Table . DiseaseModels with two-way interactions between gender and group were fitted and Bayesian estimates of the HRs, ages at which specific proportions of the different comparison groups were disease-free and gain of disease-free survival were computed using Markov Chain Monte Carlo , as in . UninforAll analyses were conducted in OpenBugsTable Figures Table Female NECS controls had decreased risk of cancer compared to male NECS controls . Similarly, female LLFS probands and siblings had decreased risk of cancer compared to male probands and siblings  but gender did not modify the risk for cancer in the other groups. The HR for cancer in female probands and siblings of the LLFS was 0.28 compared to female NECS controls  and even smaller for male probands and siblings compared to male NECS controls . The HR for cancer of male NECS centenarians was 0.13 compared to male NECS controls  and 0.18 for female NECS centenarians compared to female NECS controls . Figure In both the NECS and LLFS, female controls had lower risk of CVD compared to male controls Table , compareGender did not significantly change the risk for severe dementia in NECS controls and LLFS subjects, while female NECS centenarians had higher risk for dementia than male NECS centenarians . LLFS subjects had lower risk of dementia compared to NECS controls . The risk was slightly lower than the risk of severe dementia in NECS centenarians relative to NECS controls. The lower risk for dementia of LLFS subjects relative to NECS controls translated into a gain of 8.8–13.4 years in age at which 25% of the LLFS subjects had severe dementia compared to NECS controls . Compared to NECS controls, LLFS spouses had smaller risk of diabetes, and so did NECS centenarians (HR: 0.08) Table . The estThe risk for hypertension was significantly smaller in LLFS probands and siblings than NECS controls . NECS centenarians had similar change in risk compared to NECS controls: HR: 0.15  in male centenarians relative to male NECS controls and HR: 0.17  in female centenarians relative to female NECS controls. Female NECS centenarians also had greater risk for hypertension relative to male centenarians although the increase was only marginally significant . The risk for hypertension in LLFS female spouses was 0.56 times the risk in NECS controls  and smaller in males . LLFS probands and siblings delayed the age at which 25% subjects had hypertension by about 18 years compared to controls from the NECS  and 0.49 when compared to female NECS controls . The risk was smaller in NECS male centenarians  relative to male NECS controls and relative to female NECS controls . The age at which 25% of controls had a stroke event was approximately 87 years for males and approximately 95 years for females, 98 years for LLFS probands and siblings and >105 years in NECS centenarians.The onset of morbidity was delayed in female NECS controls compared to male NECS controls, and in LLFS and NECS subjects compared to controls Figure . HoweverThe analysis showed that LLFS probands and siblings markedly delay the age of onset of major age-related diseases relative to NECS controls. The LLFS subjects’ overall disease-free survival was almost comparable to that of NECS centenarians with the exception of severe dementia where the LLFS subjects demonstrated an even greater delay. This finding could be due to the LLFS inclusion criterion that required the proband and at least one sibling to be able to provide their own consents at the time of enrollment. Pulmonary disease was much less prevalent in LLFS probands and siblings and NECS centenarians (5%) compared to NECS controls and this result supports the importance of pulmonary health for longevity and the fact that poor pulmonary function is a strong predictor of mortality , 13.A similar pattern of delay in age of onset was observed for nearly all the age-related diseases included in these analyses. Perhaps members of these families age at slower rates and they have biological factors that impact upon both rate of aging and pathogeneses of age-related diseases. In general, women delay age-related diseases such as CVD and stroke by about 5–10 years compared to men . HoweverA surprising result of the analysis was the delay in onset of morbidity of the LLFS spouses. This delay could be due to the fact that at enrollment, the spouses have already achieved ages substantially beyond average life expectancy for their cohort. The spouses might also share environmental factors and life styles of LLFS probands and siblings that are conducive to increased health-span. Additional analyses that correlate environmental and genetic factors to the health-spans of these subjects will be necessary to understand this result .This study aimed at comparing the health-spans of LLFS subjects relative to NECS controls and centenarians without trying to discover risk factors associated with the different patterns of survival. Future analyses that integrate genetic and non-genetic data will be necessary to discover factors that promote and extend health-span. The study described here establishes the LLFS as an invaluable resource to discover genetic and environmental factors that promote exceptional health-span and life-span.A limitation of this study is that we relied upon self-report for ascertainment of the ages of onset of the various diseases. However for all of the diseases included in the analysis, there was a very strong correlation between these reports and the subjects’ medical records for a subsample of NECS subjects. Also, all participants were subjected to similar methods of data collection and therefore, comparisons between them should still yield valid results, at least relative to one another. The problem of likely decreased sensitivity associated with self-report for diseases such as dementia and stroke can be minimized in future analysis of LLFS data by relying upon direct functional and diagnostic measures that have been performed on all subjects. Unfortunately, these do not help us in determining age of onset for diseases that have already become clinically evident.An additional limitation is that this analysis combines reported medical history with prospectively collected data about onset of diseases in highly selected subjects, so that the HRs comparing subjects selected for familial longevity to controls selected for lack of familial longevity may be influenced by a survivor effect. Although this limitation does not affect the comparative description of the health-span of the study subjects and provides evidence that the LLFS is a valuable resource for studies of healthy aging and longevity, the magnitude of the HRs may not be directly applicable to the general population. The study subjects are currently followed up and future analyses of the offspring cohort will provide more general results.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.http://www.frontiersin.org/Epidemiology/10.3389/fpubh.2013.00038/abstractThe Supplementary Material for this article can be found online at


Genetic pathways underlying the initiation and progression of age-related macular degeneration (AMD) have not been yet sufficiently revealed, and the correlations of AMD's genotypes, phenotypes, and disease spectrum are still awaiting resolution. We are tackling both problems with systems biology phylogenetic parsimony analysis. Gene expression data  of macular and extramacular specimens of the retinas and retinal pigment epithelium (RPE) choroid complexes representing dry AMD without geographic atrophy (GA), choroidal neovascularization (CNV), GA, as well as pre-AMD and subclinical pre-AMD were polarized against their respective normal specimens and then processed through the parsimony program MIX to produce phylogenetic cladograms. Gene lists from cladograms' nodes were processed in Genomatix GePS to reveal the affected signaling pathway networks. Cladograms exposed a highly heterogeneous transcriptomic profiles within all the conventional phenotypes. Moreover, clades and nodal synapomorphies did not support the classical AMD phenotypes as valid transcriptomal genotypes. Gene lists defined by cladogram nodes showed that the AMD-related deregulations occurring in the neural retina were different from those in RPE-choroidal tissue. Our analysis suggests a more complex transcriptional profile of the phenotypes than expected. Evaluation of the disease in much earlier stages is needed to elucidate the initial events of AMD. Age-related macular degeneration (AMD) is the main cause of permanent central blindness in the developed countries . It maniAlthough a more recent clinical classification of AMD has been published recently , we are Further specific objectives of this analysis are to find out if gene expression profiling supports the current classification of phenotypes, to identify the shared gene expression aberrations among AMD's phenotypes, to find out if the transformations in the neural retina are similar to those in RPE-choroidal region, and to carry out class discovery in order to subtype AMD on the basis of gene expression profiles and answer whether it is a single disease or different disease entities.To reach the above stated objectives, we have selected parsimony phylogenetics as the best systems biology tool to analyze microarray gene expression data of AMD obtained from public domains. Parsimony is an evolutionary analytical method that has been applied to mass spectrometry data of cancer , gene-exOur analytical strategy can be summarized in the following steps: classify the patient specimens into clades (a cluster of specimens located on the cladogram) onto cladogram through parsimony analysis of their gene-expression data; identify shared genes with abnormal expression (termed synapomorphies in phylogenetic vocabulary) for each clade; and identify genetic pathways affected by abnormal gene expression for all AMD specimens and/or for each clade.http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29801). The gene expression dataset of macular and extramacular encompassed specimens of retinas  and retinal pigment epithelium (RPE-) choroid complexes  [Dataset GSE29801 was downloaded from Geo Datasets of NCBI (http://evolution.genetics.washington.edu/phylip.html) to produce phylogenetic cladograms for both datasets (for details of this process see [http://www.genomatix.de/) to reveal the affected gene signaling pathway networks.Pre-AMD and AMD gene expression values of retinal and RPE-choroidal specimens were polarized separately against their respective normal specimens , and the new polarized data matrices were processed separately through MIX , a parsicess see , 13). ThFor a more meaningful interpretation of the affected signaling pathways, our analysis focused on sampling different regions of the cladograms to reveal the diversity of the affected signaling pathways within AMD lesions. After the extraction of the synapomorphies at several locations of cladograms 1 and 2, we extrapolated from the synapomorphies the affected signaling pathways Tables  and 4 byEach dataset analysis with MIX produced over 100 cladograms, and only one cladogram was selected  to represent each analysis Figures . InteresThe specimens of each AMD phenotype did not cluster together to form a clade  but rather formed mixed clades that encompassed several phenotypes Figures  and 2. TMacular and temporal extra-macular tissues of the same patient separated in most of the retinal and RPE-choroid complex sets but some clustered together (12–15%) indicating similar changes in both locations (macular and extramacular). This could be attributed to the diversity of the disease itself where it is similar in both locations in some patients and different in others, or could be due to sampling from similar locations.The two cladograms Figures  and 2 deExcept for the majority of the retina AMD specimens (both macular and extramacular) that shared 113 synapomorphies (shared gene expression aberrations) most of the genetic aberrations were specimen-specific; however, there were a few synapomorphies defining a number of clades. Since AMD phenotypes did not form their respective clades, there were not any synapomorphies that defined any of the phenotype. While the retina clade was defined by 113 synapomorphies the RPE-choroid complex clade had only two synapomorphies; these are located at the basal section of the cladograms Figures .Tables http://www.ncbi.nlm.nih.gov/gene/. Unfortunately, since the cladograms of Figures The samples of This study is the first transcriptomal analysis of the retina and RPE-choroid complex tissues from AMD patients and normal subjects by means of phylogenetic parsimony. The method is a data-based (not specimen-based) analytical paradigm that produces a hierarchical modeling of the specimens into clades (phylogenetic clusters) defined by their shared aberrations, which when identified reveal the affected signaling pathways. The parsimony cladogram is multidimensional tool that exposes the characteristics of its data. In this study, the large number of equally parsimonious cladograms that were produced from the two datasets displayed the massive heterogeneity of the expression pattern within or across the clinical classification of AMD. Each dataset produced over 100 cladograms, an unusually high number of cladograms for a dataset of anatomically-related specimens. However, such diversity in advanced degenerative disease could be expected since these diseases are a downhill path toward undifferentiation due to the deregulation of differentiation pathways, and their phenotypes can be reached through several ontogenic pathways. AMD follows the same pattern, and it should not be unexpected that its specimens have shown this considerable heterogeneity. However, it may be surprising to find that the transcriptional profiles of both datasets did not support the current classification of the AMDs phenotypes and that the neural retina is different from the RPE-choroid complex in their deregulated pathways. The clades produced by the parsimony algorithm did not even come close to the classification of Newman et al.  as evidePathological aberrations in general are usually divided into driver  and passenger (nonexpanded) . On a clOur analysis is fundamentally different from that of Newman et al. who mainly used fold change ≥1.5) as their criteria to identify significantly expressed genes in AMD phenotypes. Ours differs in that we used the normal range of gene expression  as the cutoff for determining the under-and overexpressed genes per specimen. This was followed by a phylogenetic stratification of AMD retinal and RPE-choroid specimens to find the natural clusters (clades) and their affected pathways for each of the two groups of specimens. Since these two methods belong to two different schools of thought (specimen-based versus data-based), the congruence of their results was very weak. Therefore, gene lists and pathways of Newman et al. differed from ours. Furthermore, while Newman et al. claimed that their results supported the current phenotypic classification of AMD, we think that our unsupervised analysis did not support AMD's phenotypes .5 as the. As our AMD like all degenerative diseases can be bioinformatically modeled on a cladogram as a spectrum that ranges from early stages with initial events to advanced stages with later events. When specimens representing all stages of AMD are used to construct a cladogram, the ones harboring early stages of the disease will occupy the basal location of the cladogram while later stages follow. Therefore, revealing early events of AMD  requires the study of specimens that are less advanced in their pathology . In thisIn spite of some slight overlap, the affected signaling pathways in AMD are different in the retina and RPE-choroid complex Tables  and 4. IIn conclusion, AMD appears to be a diverse disease that involves two major independent but parallel pathological processes, one within the neural retina and the other within the RPE-choroid complex. In both areas, the transcriptomal changes are very heterogeneous and seem to be mostly patient-specific and involve various signaling pathways. Furthermore, the transcriptomal profiles seem to be incongruent with the clinical phenotypes, and the early gene expression events of AMD cannot be deciphered from the advanced phenotypes of the disease.


The zebrafish has emerged as an important model of heart development and regeneration. While the structural characteristics of the developing and adult zebrafish ventricle have been previously studied, little attention has been paid to the nature of the interface between the compact and spongy myocardium. Here we describe how these two distinct layers are structurally and functionally integrated. We demonstrate by transmission electron microscopy that this interface is complex and composed primarily of a junctional region occupied by collagen, as well as a population of fibroblasts that form a highly complex network. We also describe a continuum of uniquely flattened transitional cardiac myocytes that form a circumferential plate upon which the radially-oriented luminal trabeculae are anchored. In addition, we have uncovered within the transitional ring a subpopulation of markedly electron dense cardiac myocytes. At discrete intervals the transitional cardiac myocytes form contact bridges across the junctional space that are stabilized through localized desmosomes and fascia adherentes junctions with adjacent compact cardiac myocytes. Finally using serial block-face scanning electron microscopy, segmentation and volume reconstruction, we confirm the three-dimensional nature of the junctional region as well as the presence of the sheet-like fibroblast network. These ultrastructural studies demonstrate the previously unrecognized complexity with which the compact and spongy layers are structurally integrated, and provide a new basis for understanding development and regeneration in the zebrafish heart. The zebrafish heart consists of a spongy ventricular myocardium made of trabecular bundles projecting radially into the ventricular lumen, and of an outer compact heart layer that encases the spongy trabeculae. The proportion of spongy to compact heart varies significantly between fish and appears to strongly correlate to each species particular ecological physiology The zebrafish has emerged as an important model of heart development and regeneration. The adult zebrafish heart is a type-2 heart with a compact layer perfused by capillaries. An extensive number of studies have provided insights into the molecular mechanisms underlying the development of the zebrafish ventricle Studies in a variety of fish using different approaches have resulted in markedly diverse understandings and models of this interface region. Early studies in the albacore tuna suggested that the two myocardial layers were attached by a connective tissue layer The purpose of our study was to ascertain the cellular and ultrastructural nature of the interface region between compact and spongy heart of adult zebrafish using light and transmission electron microcopy (TEM). Here, we provide evidence of a complex and previously unrecognized JR containing a network of fibroblasts, a subpopulation of phenotypically transitional cardiac myocytes at the base of the spongy myocardium, and describe the spatial distribution of adherens junctions linking the spongy and compact layers. The three-dimensional structure of the JR was confirmed by serial block-face scanning electron microscopy (SBF-SEM) and computerized segmentation. To our knowledge, this is the first detailed description of the JR of the zebrafish ventricle, as well as the first ultrastructural 3D reconstruction of this region using SBF-SEM.Zebrafish were obtained from Aquatic Research Organisms , and maintained in 10-gallon tanks, with 15 to 20 fish per tank, at 28 degrees Celsius on a 14/10 hour day/night cycle. Experimental procedures were approved by the Committee for the Care and Use of Laboratory Animals at DePauw University.−4 g/kg dose of diltiazem for 4 hours. The hearts were then post-fixed in 2% osmium tetroxide, dehydrated, and embedded in Spurr’s epoxy resin. Ultra-thin sections 100 nm thick were cut and mounted on single slot or 200-mesh copper or nickel grids and imaged on a Tecnai G2 Spirit BioTWIN electron microscope .For studies of the myocardium in plastic sections and by transmission electron microcopy tissue samples were processed as described previously Following isolation, zebrafish hearts were cryoprotected in 30% sucrose in PBS overnight. The following day, the hearts were embedded in freezing medium , kept at −80 degrees C and later sectioned using a Leica CM 1900 cryostat . Ten-micron sagittal sections were fixed for 3 minutes in 4% paraformaldehyde, permeabilized with 0.5% triton X in PBS, blocked with 3% BSA for 2 hours, and immunoreacted overnight with anti-MYH1 antibody or MEF antibody , followed by Texas-Red conjugated anti-mouse or anti-rabbit secondary antibody. Next, the sections were incubated with FITC-labeled wheat germ agglutinin  for 2 hours. Other sections were stained with TRITC-labeled WGA. Following Hoechst staining, sections were imaged on a Zeiss Axio Imager.M  or a Leica TCS SP5 confocal microscope .Tissue fixation and embedding were performed using the previously published protocols with some modifications To determine the nature of the interface region between the compact and spongy heart of the adult zebrafish, we first studied the ventricle under light microscopy. Using two-micron thick toluidine blue-stained plastic embedded sections, we observed the expected organization: a relatively thin layer of the compact heart (approximately 10–20 um thick) framing the trabeculae which projected radially into the ventricular lumen . A. HoweThe EDTCM were in direct contact with the ETTCM . A. WithWe further investigated the nature of the arrangement between the transitional CM ring and the CM forming the trabeculae. Transitional CM can be found linked to trabecular myocytes through a variety of adherens junctions. These junctions included fascia adherentes . A, B thThe transitional ring of myocytes on its abluminal side is bounded by a narrow (0.5–1 um) connective tissue space. This space separates the EDTCM and ETTCM from the adjacent CM of the compact layer, creating a junctional space within the JR . A. The The fibroblasts were also found in close proximity or in direct contact with parallel or perpendicularly-oriented collagen fibers . B, C. AFrom our observations, we estimated that the junctional space containing fibroblasts and collagen occupies 80 to 90% of the junctional region between compact and spongy heart, so that the majority of the CM membranes in the transitional ring are not directly linked to the compact heart. The remaining portion of the spongy-compact interface consisted of cell membrane appositions between transitional CM and the most adjacent CM of the compact heart . A. ThesTo better assess the three-dimensional architecture of the junctional region and confirm the three-dimensional nature of the fibroblast network, we performed serial block-face scanning electron microcopy (SBF-SEM) of the adult zebrafish heart. A preparatory survey of the fibroblast network in the JR of the zebrafish ventricle was performed by TEM in 100 nm sections from heavy metal-contrasted Durcupan-embedded hearts. The junctional region and the fibroblasts were easily identifiable. Image stacks generated with the FEI Quanta 200 FEG SEM equipped with the Gatan 3View . A were This paper documents a previously unrecognized connective tissue space located at the interface of the spongy and compact myocardial of the adult zebrafish heart. It extends our understanding of the cellular and ultrastructural nature of the ventricular JR of an important research model. The existence of a connective tissue layer in the junctional region of type-2 fish hearts has remained controversial. A continuous fibrous membrane interposed between the compact and spongy layers has been reported in the hearts of tuna Our ultrastructural observations reveal a junctional space measuring for the most part less than one micrometer wide, populated by a single layer of fibroblasts organized into a network, and framed by CM belonging the compact myocardium distally and the spongy myocardium proximally. Fibroblasts are an important component of the mammalian heart and play an essential role in heart structure and physiology. They are a source of extracellular matrix molecules and growth factors, and they serve as sensors for mechanical signals Fibroblast networks have been documented in a variety of organs and species, with direct fibroblast-fibroblast contacts being observed in mammalian corneas The present study also establishes that the junctional space occupies the majority of the overall SCI, and creates an extensive volume of non-contact between the two myocardial layers. Given the sparsity of the collagen fibers observed in the junctional space, we question whether in the zebrafish, the connective tissue would provide sufficient support to maintain the structural integrity of the two layers. We speculate that the connective tissue compartment may not be the primary mechanism by which adhesion between the two myocardia is maintained. Indeed, the junctional space is interrupted by contact bridges between the two layers at discrete intervals through membrane apposition of adjacent CM, and that desmosomes and fascia adherentes are frequently found within the contact regions between transitional zebrafish CM and compact CM. These findings are consistent with the demonstration of highly enriched adhesion junction molecules between the two myocardial layers observed in salmon and trout An important finding is the transitional ring of cardiac myocytes similar to that previously described by Midtunn, that underscores the phenotypic diversity of cardiac myocytes present in the zebrafish heart, suggesting specific structure-function relationship. The notion of cardiac myocyte diversity is apparent in recent work demonstrating the clonal contribution of cardiac myocytes to the emergence of the zebrafish heart In conclusion, this study sheds light on the phenotypic diversity of CM at the JR of the adult zebrafish heart. It documents the existence of a fibroblast network that contributes to the architectural complexity of the region . We suggFigure S1Transitional myocyte abluminal caveolae. (A), Junctional space (JS) with a fibroblast process (FP). (B), Higher magnification of inset in (A) showing caveolae (*) on transitional CM facing the JS.(TIF)Click here for additional data file.Movie S1Architecture of the junctional region of zebrafish heart. The sheet-like nature of fibroblasts can be appreciated.(MP4)Click here for additional data file.Movie S2Segmented fibroblasts and transitional CM.(MP4)Click here for additional data file.


The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate.We compare several widely used normalization approaches  applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures.T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially. For over a decade, two-channel transcriptomics microarrays have provided a powerful approach to study genome-wide gene expression events. Now, continued development of two-channel microarray technology has enabled extending our experimentation to the next level: regulation of gene transcription. One of the most popular techniques in this field combines chromatin immunoprecipitation (ChIP) assays with two-channel microarray technology (ChIP-on-chip ). ChIP-oEven though newer technologies such as ChIP-sequencing (ChIP-seq) are on the rise, two-channel microarrays still present a valuable approach to understanding gene transcription regulation events, and during the last decade have opened opportunities to identify novel targets and markers in complex diseases such as cancer -5, heartThe design and the experimental approach for regulation microarrays are very different from the more extensively studied transcriptomics microarrays, which has implications for data pre-processing procedures. The key difference is that in transcriptomics microarrays both channels contain amplified transcript samples, usually corresponding to two different experimental conditions, while in regulation microarrays the channels comprise an experimental sample and a reference sample. The cyanine 3 (Cy3), or green, channel of regulation microarrays generally contains the total DNA sample that gives the reference baseline signal, and the cyanine 5 (Cy5), or red, channel contains an experimentally enriched DNA sample, extracted using a specific antibody binding to a DNA-interacting protein (ChIP) or directly to methylated CpGs on the DNA (MeDIP). Hence, while the log-ratio between the channel signals represents the differential expression between two conditions in transcriptomics studies, for regulation microarrays it is used as a measure of enrichment: the higher the log-ratio of a probe or set of tiling probes, the higher the likelihood that the corresponding region in the genome has a high level of methylation or is targeted by a DNA-interacting protein.Another important assumption in regulation microarrays is that a DNA-interacting protein is either bound or not bound (for ChIP) and that a target sequence is either methylated or not (for MeDIP). Regardless, depending on binding affinity, mean time of residence and other factors, the fraction of cells with bound protein or a particular methylation status is not an all-or-nothing condition, especially in heterogeneous tissues. Combined with the characteristics of the data distribution surrounding a site of interest Figure  and probNormalization is a process that is applied at multiple levels connected to spatial , probe -15 and dBased on these observations, the main challenge of the normalization of regulation microarrays is (i) to make the signals of individual microarrays quantitatively comparable and (ii) to retain the separation between the enriched and un-enriched components present in the data. Programs like CoCAS  offer a To determine the efficacy in correcting for technical biases and improving comparability between microarrays, quality control and bias assessment was performed on all datasets before and after normalization for each of the six normalization approaches. Complete results are available in additional file Methods section for dataset details and numbering) shows largely overlapping control probe and gene promoter probe distributions  show equal performance of all approaches for dataset #1 Figure , resultiDataset #2, the second ChIP-on-chip dataset gives different results Figure  and 4b. Tukey's biweight scaling and T-quantile normalization appear to perform comparably with respect to conserving the component separation. Tukey's biweight scaling adjusts the log-ratio data with a scaling factor for each microarray in the dataset individually, which means that the ROC curves will be identical to those of the raw data, and that the distributions will be the same as those before normalization save for a shift. This may explain the variability observed in the individual ROC curves and AUC values of the Tukey's biweight scaling normalized data. T-quantile normalization reduces the variability between the data distributions of individual microarrays, resulting in ROC curves that are more comparable in both shape and AUC Figure .The results of the MeDIP-on-chip datasets support the conclusions reached for the ChIP-on-chip datasets: separation of the components present before normalization Figure  and 3e aAny appropriate normalization method should preserve the biological information present in the raw data. Assessing the distributions of the negative control probes and the gene promoter probes is a global indicator of this conservation of biological information. In addition, three datasets with suitable positive controls were used to assess the impact of the normalization approaches on the power to identify significant enrichment for specific genomic regions. ACME  was used10log-transformed enrichment p-values plotted along the HOXA region are shown in Figure top). Using Tukey's biweight scaling or T-quantile normalization results in identification of several enriched loci, most of which are moderately methylated. Less loci are found when using VSN, quantile or LOWESS normalization. Peng's method results in identification of only a few loci with moderate enrichment.For dataset #3 enrichment of the HOXA group of developmental genes was calculated. HOXA genes are located in a cluster on chromosome 7 and are known to be switched off and moderately to highly methylated in most tissues . The negbottom).For dataset #4 enrichment was determined for the Dlk1-Gtl2 cluster on chromosome 12, a region reported in the original results  to be hi8Two-channel transcriptomics and regulation microarrays should not be pre-processed in the same manner. Appropriate normalization strategies for regulation microarrays are characterized by their ability to retain the separation between the enriched and un-enriched components present in the data whilst enhancing comparability between microarrays. Six normalization methods were tested by (i) assessing the separation between the control probe and gene promoter probe distributions before and after normalization using ROC curves and (ii) by verifying whether known enriched genes and regions could be identified as such after normalization. We have shown that the result of each approach depends heavily on the situation before normalization, specifically the amount of enriched and un-enriched probes and the separation between the corresponding components in the raw data. These two characteristics are different for each experiment, depending largely on the biological system studied and the applied assay.In the ChIP-on-chip datasets used here, the distributions of the control probes and gene promoter probes overlap to a large extent before and after normalization. This may be explained by the small proportion of the genome generally covered by the potential binding sites of a DNA-interacting protein and the resulting small contribution of the enriched component. Hence in general, the lower the amount of binding sites, the more similar the control probe and gene promoter distributions, and the more comparable the performance of the normalization approaches, based on ROC curves of both distributions before and after normalization. However, in some cases VSN can cause a sizeable rescaling of the distributions, and to a spurious control probe distribution with a higher mean and spread than the gene promoter probe distribution. This renders gene promoter probes in the upper quantile of the data indistinguishable from random data, strongly impacting the biological interpretation.In DNA methylation microarrays the amount of enriched probes and un-enriched probes is of the same order, since in general the proportion of methylated CpG di-nucleotides in a genome is substantial. We have shown that for such microarrays, the choice for a normalization procedure will be crucial for the downstream analysis. All three MeDIP-on-chip datasets show a large degree of separation between the gene promoter and control probe distributions. The separation is lost when using normalization methods that normalize channels together, such as VSN, LOWESS, Peng's method and quantile normalization. Using LOWESS approaches on MeDIP-on-chip data has been reported elsewhere to result in increased bias, because the underlying assumption that the log-ratio should be independent of the average individual channel signals does not hold for this type of data. DNA methylation levels are related to CpG and GC density, while signal intensity is also known to be influenced by GC content. Forcing the log-ratio to be independent of the average signal intensity using LOWESS normalization thus introduces bias instead of removing it .T-quantile normalization, applied separately on the channels, and Tukey's biweight scaling are the only approaches that are able to preserve the component separation in all example datasets. In dataset #1, individual microarrays already showed comparable distributions before normalization; hence for this dataset, Tukey's biweight scaling would be sufficient. In contrast, dataset #4 for example showed a large heterogeneity between individual microarrays, in which case between-microarray normalization is better suited to improve the overall comparability and enable quantitative data comparison. This can be achieved either by doing an additional normalization step after scaling, but ideally by using a between-microarray normalization approach from the beginning, such as applying T-quantile normalization as demonstrated here.In regulation microarrays the sequence content of the input DNA sample and the experimental DNA sample always differs to a large extent. There are also instances for transcriptomics microarrays, such as dedicated microarrays designed for a specific biological context, where the assumption that the majority of genes are not differentially expressed does not hold, hence requiring adapted normalization strategies. Most of these strategies involve the use of invariant genes, either present on the slide ,30 or deThe research described herein is limited to the normalization of replicate microarrays. In many cases however, a study will consist of multiple conditions, such as different tissues, or treatment and control samples as demonstrated in dataset #1. In these cases, the experimental DNA samples may differ to a large extent between treatment and control groups, warranting application of normalization to each condition separately. However, when only a relatively small amount of loci is expected to be differentially enriched and the total amount of enrichment can be assumed constant between conditions, normalization approaches applied to the dataset as a whole are more appropriate. This holds for experiments such as DNA methylation studies on the same tissue treated with a micronutrient , where oThe results of known targets and enriched regions show consistent differences between the various normalization approaches. When looking at the Dlk1-Gtl2 cluster for the DNA methylation data of dataset #4, a region reported to be highly enriched in the original findings, it is clear that such highly enriched regions will be identified as such regardless of the chosen normalization approach. This is not the case when studying moderately enriched regions, as illustrated by the results of the HOXA cluster in dataset #3, where the degree to which this region is identified as being enriched depends strongly on the applied normalization approach. Overall, T-quantile normalization and Tukey's biweight scaling again give the best results. A potential cause of the observed difference between the tested normalization approaches is observed in the results on global level: the ranking of probes changes when using some normalization approaches, increasing the likelihood of un-enriched probes being spread over the whole dynamic range of the enriched probe distribution. Ultimately, such changes in the ranking can be destructive on the power to call differences in methylation or protein binding. Also, enrichment finding algorithms  as used The main issue of ChIP-on-chip and DNA methylation microarray normalization is to enhance comparability between microarrays, while keeping the separation between the enriched and un-enriched components present in the data. Within-channel approaches give the best performance, with enhanced comparability between individual microarrays for approaches that also normalize between microarrays. More specifically, quantile, LOWESS, Peng's and VSN normalization alter the signal distributions to such an extent that it will impact the reliability of the downstream analysis substantially. Better results are obtained with T-quantile normalization applied separately on the channels or Tukey's biweight scaling. For all datasets tested, these two methods consistently outperform the other tested methods in conservation of separation between the enriched and un-enriched distributions, as well as in identification of genomic regions known to be enriched. The T-quantile approach is preferable because it additionally yields enhanced comparability between microarrays.Five published datasets were selected from ArrayExpress. Selection criteria were set to select several assay types (MeDIP and ChIP), several species (human and mouse) and cover several research fields. Due to the selection criteria, all datasets were chosen from the same microarray manufacturer, NimbleGen table .Sub-selections of microarrays and experimental groups were made to keep only the microarrays of sufficient quality and homogeneous replicate groups of sufficiently large size. In dataset #1, one microarray of the 17beta-estradiol stimulated group was removed because the red channel was saturated, as reported previously . Insteadhttp://www.bigcat.unimaas.nl/userfiles/adriaens/arrayQualityMetrics/.Quality control and bias assessment of the raw and normalized data was performed using the arrayQualityMetrics package . IndividMicroarray data is subject to multiple sources of variation. The goal of normalization is to remove all technical biases from the microarray data, while retaining the biological variation. There are many normalization procedures available for two-channel microarray data, but the choice for a specific procedure has to be fuelled by the characteristics of the dataset: (i) the procedure should correct all the systematic biases in the dataset diagnosed during the quality control process and (ii) the underlying assumptions of the particular method must be met. In regulation studies, there is the additional goal to retain the separation between the enriched and un-enriched components of the log-ratio distribution.To illustrate this, data from five human and mouse ChIP-on-chip and MeDIP-on-chip datasets were normalized using six different methods: (i) LOWESS normalization ,16 appliNimbleGen uses Tukey's biweight scaling in-house. It consists of two steps: calculating the log-ratio between channels and subsequently correcting these by subtracting the robust Tukey's biweight estimate of the median. For this estimate, each data point is given a weight using a bi-square function. The weights assigned by this function are inversely correlated to the distance from the median, so outliers have a minimal effect on the estimate. The method developed by Peng et al.  makes stThe separation between the enriched and un-enriched components present in the data of two-channel regulation microarrays should be conserved after applying normalization. To determine this conservation, the log-ratio distribution of negative control probes  and the log-ratio distribution of gene promoter probes were assessed before and after normalization using ROC curves. For creating the ROC curves, the negative control probes represent the negative class of outcomes, while the gene promoter probes represent the positive class of outcomes. If there are any enriched probes, the gene promoter probe distribution should extend beyond the control probe distribution in the upper quantile and is expected to have a higher mean than the control probe distribution. If this separation is retained, the ROC curves are expected to have comparable AUC values before and after normalization, while if the separation is not retained, the ROC curves will have lower AUC values after normalization.a priori to be enriched were used as positive controls, verifying to what extent these regions are identified after using each of the six normalization approaches. To this end, 33 well established ER-a targets [Genomic regions known  targets  were cho targets . Enrichm targets . For dat targets . Enrichm targets . The othData was imported and analyzed using Bioconductor  in the sMA and MJ carried out the analysis and interpretation of the microarray data and wrote the manuscript. CM, LE and CE helped drafting the manuscript and advised on the technical aspects and interpretation of the results. CE coordinated the project. All authors have read and approved the final manuscript.ArrayQualityMetrics quality control and bias assessment results (part 1). A ZIP file containing a folder with the results of the quality control and bias assessment generated with the arrayQualityMetrics package for datasets #1 and #2. The results are formatted as webpages. Individual results can be accessed by opening the 'index.html' file in any subfolder. An overview of all results can be accessed by combining the contents of the main folder in additional file 1 with the contents of the main folder of additional file 2, and subsequently opening the 'index.html' file in the main folder.Click here for fileArrayQualityMetrics quality control and bias assessment results (part 2). A ZIP file containing a folder with the results of the quality control and bias assessment generated with the arrayQualityMetrics package for datasets #3, #4 and #5. The results are formatted as webpages. Individual results can be accessed by opening the 'index.html' file in any subfolder. An overview of all results can be accessed by combining the contents of the main folder in additional file 1 with the contents of the main folder of additional file 2, and subsequently opening the 'index.html' file in the main folder.Click here for file