Pathological and Physiological High-frequency Oscillations on Electroencephalography in Patients with Epilepsy

High-frequency oscillations (HFOs) encompass ripples (80 Hz-200 Hz) and fast ripples (200 Hz-600 Hz), serving as a promising biomarker for localizing the epileptogenic zone in epilepsy. Spontaneous fast ripples are always pathological, while ripples may be physiological or pathological. Distinguishing physiological from pathological ripples is important not only for designating epileptogenic brain regions, but also for investigations that study ripples in the context of memory encoding, consolidation, and recall in patients with epilepsy. Many studies have sought to identify distinguishing features between pathological and physiological ripples over the past two decades. Physiological and pathological ripples differ with respect to their spatial location, cellular mechanisms, morphology, and coupling with background electroencephalographic activity. Retrospective studies have demonstrated that differentiating between pathological and physiological ripples can improve surgical outcome prediction. In this review, we summarize the characteristics, differences, and applications of pathological and physiological HFOs and discuss strategies for their clinical translation.

Pathological neurons generate ripples at the UP-DOWN transition disrupting information transfer

OBJECTIVE

To confirm and investigate why pathological high-frequency oscillations (pHFOs), including ripples (80-200 Hz) and fast ripples (200-600 Hz), are generated during the UP-DOWN transition of the slow wave and if information transmission mediated by ripple temporal coupling is disrupted in the seizure-onset zone (SOZ).

METHODS

We isolated 217 total units from 175.95 intracranial electroencephalography (iEEG) contact-hours of synchronized macro- and microelectrode recordings from 6 patients. Sleep slow oscillation (.1-2 Hz) epochs were identified in the iEEG recording. iEEG HFOs that occurred superimposed on the slow wave were transformed to phasors and adjusted by the phase of maximum firing in nearby units (i.e., maximum UP). We tested whether, in the SOZ, HFOs and associated action potentials (APs) occur more often at the UP-DOWN transition. We also examined ripple temporal correlations using cross-correlograms.

RESULTS

At the group level in the SOZ, HFO and HFO-associated AP probability was highest during the UP-DOWN transition of slow wave excitability (p < < .001). In the non-SOZ, HFO and HFO-associated AP was highest during the DOWN-UP transition (p < < .001). At the unit level in the SOZ, 15.6% and 20% of units exhibited more robust firing during ripples (Cohen's d = .11-.83) and fast ripples (d = .36-.90) at the UP-DOWN transition (p < .05 f.d.r. corrected), respectively. By comparison, also in the SOZ, 6.6% (d = .14-.30) and 8.5% (d = .33-.41) of units had significantly less firing during ripples and fast ripples at the UP-DOWN transition, respectively. Additional data shows that ripple and fast ripple temporal correlations, involving global slow waves, between the hippocampus, entorhinal cortex, and parahippocampal gyrus were reduced by >50% in the SOZ compared to the non-SOZ (N = 3).

SIGNIFICANCE

The UP-DOWN transition of slow wave excitability facilitates the activation of pathological neurons to generate pHFOs. Ripple temporal correlations across brain regions may be important in memory consolidation and are disrupted in the SOZ, perhaps by pHFO generation.

Fast ripples reflect increased excitability that primes epileptiform spikes

The neuronal circuit disturbances that drive inter-ictal and ictal epileptiform discharges remain elusive. Using a combination of extra-operative macro-electrode and micro-electrode inter-ictal recordings in six pre-surgical patients during non-rapid eye movement sleep, we found that, exclusively in the seizure onset zone, fast ripples (200-600 Hz), but not ripples (80-200 Hz), frequently occur <300 ms before an inter-ictal intra-cranial EEG spike with a probability exceeding chance (bootstrapping, P < 1e-5). Such fast ripple events are associated with higher spectral power (P < 1e-10) and correlated with more vigorous neuronal firing than solitary fast ripple (generalized linear mixed-effects model, P < 1e-9). During the intra-cranial EEG spike that follows a fast ripple, action potential firing is lower than during an intra-cranial EEG spike alone (generalized linear mixed-effects model, P < 0.05), reflecting an inhibitory restraint of intra-cranial EEG spike initiation. In contrast, ripples do not appear to prime epileptiform spikes. We next investigated the clinical significance of pre-spike fast ripple in a separate cohort of 23 patients implanted with stereo EEG electrodes, who underwent resections. In non-rapid eye movement sleep recordings, sites containing a high proportion of fast ripple preceding intra-cranial EEG spikes correlate with brain areas where seizures begin more than solitary fast ripple (P < 1e-5). Despite this correlation, removal of these sites does not guarantee seizure freedom. These results are consistent with the hypothesis that fast ripple preceding EEG spikes reflect an increase in local excitability that primes EEG spike discharges preferentially in the seizure onset zone and that epileptogenic brain regions are necessary, but not sufficient, for initiating inter-ictal epileptiform discharges.

Pathological neurons generate ripples at the UP-DOWN transition disrupting information transfer

Objective

To confirm and investigate why pathological HFOs (pHFOs), including Ripples [80-200 Hz] and fast ripples [200-600 Hz], are generated during the UP-DOWN transition of the slow wave and if pHFOs interfere with information transmission.

Methods

We isolated 217 total units from 175.95 iEEG contact-hours of synchronized macro- and microelectrode recordings from 6 patients. Sleep slow oscillation (0.1-2 Hz) epochs were identified in the iEEG recording. iEEG HFOs that occurred superimposed on the slow wave were transformed to phasors and adjusted by the phase of maximum firing in nearby units (i.e., maximum UP). We tested whether, in the seizure onset zone (SOZ), HFOs and associated action potentials (AP) occur more often at the UP-DOWN transition. We also examined ripple temporal correlations using cross correlograms.

Results

At the group level in the SOZ, HFO and HFO-associated AP probability was highest during the UP-DOWN transition of slow wave excitability (p<<0.001). In the non-SOZ, HFO and HFO-associated AP was highest during the DOWN-UP transition (p<<0.001). At the unit level in the SOZ, 15.6% and 20% of units exhibited more robust firing during ripples (Cohen's d=0.11-0.83) and fast ripples (d=0.36-0.90) at the UP-DOWN transition (p<0.05 f.d.r corrected), respectively. By comparison, also in the SOZ, 6.6% (d=0.14-0.30) and 8.5% (d=0.33-0.41) of units had significantly less firing during ripples and fast ripples at the UP-DOWN transition, respectively. Additional data shows ripple temporal correlations, involving global slow waves, between the hippocampus, entorhinal cortex, and parahippocampal gyrus were reduced by ~50-80% in the SOZ compared to the non-SOZ (N=3).

Significance

The UP-DOWN transition of slow wave excitability facilitates the activation of pathological neurons to generate pHFOs. The pathological neurons and pHFOs disrupt ripple temporal correlations across brain regions that transfer information and may be important in memory consolidation.

Fast ripples reflect increased excitability that primes epileptiform spikes

The neuronal circuit disturbances that drive interictal and ictal epileptiform discharges remains elusive. Using a combination of extraoperative macro- and micro-electrode interictal recordings in six presurgical patients during non-rapid eye movement (REM) sleep we found that, exclusively in the seizure onset zone, fast ripples (FR; 200-600Hz), but not ripples (80-200 Hz), frequently occur <300 msec before an interictal intracranial EEG (iEEG) spike with a probability exceeding chance (bootstrapping, p<1e-5). Such FR events are associated with higher spectral power (p<1e-10) and correlated with more vigorous neuronal firing than solitary FR (generalized linear mixed-effects model, GLMM, p<1e-3) irrespective of FR power. During the iEEG spike that follows a FR, action potential firing is lower than during a iEEG spike alone (GLMM, p<1e-10), reflecting an inhibitory restraint of iEEG spike initiation. In contrast, ripples do not appear to prime epileptiform spikes. We next investigated the clinical significance of pre-spike FR in a separate cohort of 23 patients implanted with stereo EEG electrodes who underwent resections. In non-REM sleep recordings, sites containing a high proportion of FR preceding iEEG spikes correlate with brain areas where seizures begin more than solitary FR (p<1e-5). Despite this correlation, removal of these sites does not guarantee seizure freedom. These results are consistent with the hypothesis that FR preceding EEG spikes reflect an increase in local excitability that primes EEG spike discharges preferentially in the seizure onset zone and that epileptogenic brain regions are necessary, but not sufficient, for initiating interictal epileptiform discharges.

Graph theoretical measures of fast ripple networks improve the accuracy of post-operative seizure outcome prediction

Fast ripples (FR) are a biomarker of epileptogenic brain, but when larger portions of FR generating regions are resected seizure freedom is not always achieved. To evaluate and improve the diagnostic accuracy of FR resection for predicting seizure freedom we compared the FR resection ratio (RR) with FR network graph theoretical measures. In 23 patients FR were semi-automatically detected and quantified in stereo EEG recordings during sleep. MRI normalization and co-registration localized contacts and relation to resection margins. The number of FR, and graph theoretical measures, which were spatial (i.e., FR rate-distance radius) or temporal correlational (i.e., FR mutual information), were compared with the resection margins and with seizure outcome We found that the FR RR did not correlate with seizure-outcome (p > 0.05). In contrast, the FR rate-distance radius resected difference and the FR MI mean characteristic path length RR did correlate with seizure-outcome (p < 0.05). Retesting of positive FR RR patients using either FR rate-distance radius resected difference or the FR MI mean characteristic path length RR reduced seizure-free misclassifications from 44 to 22% and 17%, respectively. These results indicate that graph theoretical measures of FR networks can improve the diagnostic accuracy of the resection of FR events for predicting seizure freedom.

A consensus statement on detection of hippocampal sharp wave ripples and differentiation from other fast oscillations

Decades of rodent research have established the role of hippocampal sharp wave ripples (SPW-Rs) in consolidating and guiding experience. More recently, intracranial recordings in humans have suggested their role in episodic and semantic memory. Yet, common standards for recording, detection, and reporting do not exist. Here, we outline the methodological challenges involved in detecting ripple events and offer practical recommendations to improve separation from other high-frequency oscillations. We argue that shared experimental, detection, and reporting standards will provide a solid foundation for future translational discovery.

An approach for reliably identifying high-frequency oscillations and reducing false-positive detections

OBJECTIVE

Aiming to improve the feasibility and reliability of using high-frequency oscillations (HFOs) for translational studies of epilepsy, we present a pipeline with features specifically designed to reject false positives for HFOs to improve the automatic HFO detector.

METHODS

We presented an integrated, multi-layered procedure capable of automatically rejecting HFOs from a variety of common false positives, such as motion, background signals, and sharp transients. This method utilizes a time-frequency contour approach that embeds three different layers including peak constraints, power thresholds, and morphological identification to discard false positives. Four experts were involved in rating detected HFO events that were randomly selected from different posttraumatic epilepsy (PTE) animals for a comprehensive evaluation.

RESULTS

The algorithm was run on 768-h recordings of intracranial electrodes in 48 PTE animals. A total of 453 917 HFOs were identified by initial HFO detection, of which 450 917 were implemented for HFO refinement and 203 531 events were retained. Random sampling was used to evaluate the performance of the detector. The HFO detection yielded an overall accuracy of 0.95 ± 0.03 , with precision, recall, and F1 scores of 0.92 ± 0.05 , 0.99 ± 0.01 , and 0.94 ± 0.03 , respectively. For the HFO classification, our algorithm obtained an accuracy of 0.97 ± 0.02 . For the inter-rater reliability of algorithm evaluation, the agreement among four experts was 0.94 ± 0.03 for HFO detection and 0.85 ± 0.04 for HFO classification.

SIGNIFICANCE

Our approach shows that a segregated pipeline design with a focus on false-positive rejection can improve the detection efficiency and provide reliable results. This pipeline does not require customization and uses fixed parameters, making it highly feasible and translatable for basic and clinical applications of epilepsy.

Temporal lobe interictal spikes disrupt encoding and retrieval of verbal memory: A subregion analysis

OBJECTIVE

The medial temporal lobe (MTL) encodes and recalls memories and can be a predominant site for interictal spikes (IS) in patients with focal epilepsy. It is unclear whether memory deficits are due to IS in the MTL producing a transient decline. Here, we investigated whether IS in the MTL subregions and lateral temporal cortex impact episodic memory encoding and recall.

METHODS

Seventy-eight participants undergoing presurgical evaluation for medically refractory focal epilepsy with depth electrodes placed in the temporal lobe participated in a verbal free recall task. IS were manually annotated during the pre-encoding, encoding, and recall epochs. We examined the effect of IS on word recall using mixed-effects logistic regression.

RESULTS

IS in the left hippocampus (odds ratio [OR] = .73, 95% confidence interval [CI] = .63-.84, p < .001) and left middle temporal gyrus (OR = .46, 95% CI = .27-.78, p < .05) during word encoding decreased subsequent recall performance. Within the left hippocampus, this effect was specific for area CA1 (OR = .76, 95% CI = .66-.88, p < .01) and dentate gyrus (OR = .74, 95% CI = .62-.89, p < .05). IS in other MTL subregions or inferior and superior temporal gyrus and IS occurring during the prestimulus window did not affect word encoding (p > .05). IS during retrieval in right hippocampal (OR = .22, 95% CI = .08-.63, p = .01) and parahippocampal regions (OR = .24, 95% CI = .07-.8, p < .05) reduced the probability of recalling a word.

SIGNIFICANCE

IS in medial and lateral temporal cortex contribute to transient memory decline during verbal episodic memory.

Graph theoretical measures of fast ripples support the epileptic network hypothesis

The epileptic network hypothesis and epileptogenic zone hypothesis are two theories of ictogenesis. The network hypothesis posits that coordinated activity among interconnected nodes produces seizures. The epileptogenic zone hypothesis posits that distinct regions are necessary and sufficient for seizure generation. High-frequency oscillations, and particularly fast ripples, are thought to be biomarkers of the epileptogenic zone. We sought to test these theories by comparing high-frequency oscillation rates and networks in surgical responders and non-responders, with no appreciable change in seizure frequency or severity, within a retrospective cohort of 48 patients implanted with stereo-EEG electrodes. We recorded inter-ictal activity during non-rapid eye movement sleep and semi-automatically detected and quantified high-frequency oscillations. Each electrode contact was localized in normalized coordinates. We found that the accuracy of seizure onset zone electrode contact classification using high-frequency oscillation rates was not significantly different in surgical responders and non-responders, suggesting that in non-responders the epileptogenic zone partially encompassed the seizure onset zone(s) (P > 0.05). We also found that in the responders, fast ripple on oscillations exhibited a higher spectral content in the seizure onset zone compared with the non-seizure onset zone (P < 1 × 10⁻⁵). By contrast, in the non-responders, fast ripple had a lower spectral content in the seizure onset zone (P < 1 × 10⁻⁵). We constructed two different networks of fast ripple with a spectral content >350 Hz. The first was a rate–distance network that multiplied the Euclidian distance between fast ripple-generating contacts by the average rate of fast ripple in the two contacts. The radius of the rate–distance network, which excluded seizure onset zone nodes, discriminated non-responders, including patients not offered resection or responsive neurostimulation due to diffuse multifocal onsets, with an accuracy of 0.77 [95% confidence interval (CI) 0.56–0.98]. The second fast ripple network was constructed using the mutual information between the timing of the events to measure functional connectivity. For most non-responders, this network had a longer characteristic path length, lower mean local efficiency in the non-seizure onset zone, and a higher nodal strength among non-seizure onset zone nodes relative to seizure onset zone nodes. The graphical theoretical measures from the rate–distance and mutual information networks of 22 non- responsive neurostimulation treated patients was used to train a support vector machine, which when tested on 13 distinct patients classified non-responders with an accuracy of 0.92 (95% CI 0.75–1). These results indicate patients who do not respond to surgery or those not selected for resection or responsive neurostimulation can be explained by the epileptic network hypothesis that is a decentralized network consisting of widely distributed, hyperexcitable fast ripple-generating nodes.

Spatial and temporal profile of high-frequency oscillations in posttraumatic epileptogenesis

We studied the role of temporal and spatial changes in high-frequency oscillation (HFO, 80–500 Hz) generation in epileptogenesis following traumatic brain injury (TBI).

Experiments were conducted on adult male Sprague Dawley rats. For the TBI group, fluid percussion injury (FPI) on the left sensorimotor area was performed to induce posttraumatic epileptogenesis. For the sham control group, only the craniotomy was performed. After TBI, 8 bipolar micro-electrodes were implanted bilaterally in the prefrontal cortex, perilesional area and homotopic contralateral site, striatum, and hippocampus. Long-term video/local field potential (LFP) recordings were performed for up to 21 weeks to identify and characterize seizures and capture HFOs. The electrode tip locations and the volume of post TBI brain lesions were further estimated by ex-vivo MRI scans. HFOs were detected during slow-wave sleep and categorized as ripple (80–200 Hz) and fast ripple (FR, 250–500 Hz) events. HFO rates and the HFO peak frequencies were compared in the 8 recording locations and across 8-weeks following TBI.

Data from 48 rats (8 sham controls and 40 TBI rats) were analyzed. Within the TBI group, 22 rats (55%) developed recurrent spontaneous seizures (E+ group), at an average of 62.2 (+17.1) days, while 18 rats (45%) did not (E− group). We observed that the HFOs in the E+ group had a higher mean peak frequency than the E− group and the sham group (P < 0.05). Furthermore, the FR rate of the E+ group showed a significant increase compared to the E−group (P < 0.01) and sham control group (P < 0.01), specifically in the perilesional area, homotopic contralateral site, bilateral hippocampus, and to a lesser degree bilateral striatum. When compared across time, the increased FR rate in the E+ group occurred immediately after the insult and remained stable across the duration of the experiment. In addition, lesion size was not statistically different in the E+ and E− group and was not correlated with HFO rates.

Our results suggest that TBI results in the formation of a widespread epileptogenic network. FR rates serve as a biomarker of network formation and predict the future development of epilepsy, however FR are not a temporally specific biomarker of TBI sequelae responsible for epileptogenesis. These results suggest that in patients, future risk of post-TBI epilepsy can be predicted early using FR.

Accuracy of high-frequency oscillations recorded intraoperatively for classification of epileptogenic regions

To see whether acute intraoperative recordings using stereo EEG (SEEG) electrodes can replace prolonged interictal intracranial EEG (iEEG) recording, making the process more efficient and safer, 10 min of iEEG were recorded following electrode implantation in 16 anesthetized patients, and 1-2 days later during non-rapid eye movement (REM) sleep. Ripples on oscillations (RonO, 80-250 Hz), ripples on spikes (RonS), sharp-spikes, fast RonO (fRonO, 250-600 Hz), and fast RonS (fRonS) were semi-automatically detected. HFO power and frequency were compared between the conditions using a generalized linear mixed-effects model. HFO rates were compared using a two-way repeated measures ANOVA with anesthesia type and SOZ as factors. A receiver-operating characteristic (ROC) curve analysis quantified seizure onset zone (SOZ) classification accuracy, and the scalar product was used to assess spatial reliability. Resection of contacts with the highest rate of events was compared with outcome. During sleep, all HFOs, except fRonO, were larger in amplitude compared to intraoperatively (p < 0.01). HFO frequency was also affected (p < 0.01). Anesthesia selection affected HFO and sharp-spike rates. In both conditions combined, sharp-spikes and all HFO subtypes were increased in the SOZ (p < 0.01). However, the increases were larger during the sleep recordings (p < 0.05). The area under the ROC curves for SOZ classification were significantly smaller for intraoperative sharp-spikes, fRonO, and fRonS rates (p < 0.05). HFOs and spikes were only significantly spatially reliable for a subset of the patients (p < 0.05). A failure to resect fRonO areas in the sleep recordings trended the most sensitive and accurate for predicting failure. In summary, HFO morphology is altered by anesthesia. Intraoperative SEEG recordings exhibit increased rates of HFOs in the SOZ, but their spatial distribution can differ from sleep recordings. Recording these biomarkers during non-REM sleep offers a more accurate delineation of the SOZ and possibly the epileptogenic zone.

Stimulation of the right entorhinal white matter enhances visual memory encoding in humans

BACKGROUND

While deep brain stimulation has been successful in treating movement disorders, such as in Parkinson's disease, its potential application in alleviating memory disorders is inconclusive.

OBJECTIVE/HYPOTHESIS

We investigated the role of the location of the stimulating electrode on memory improvement and hypothesized that entorhinal white versus gray matter stimulation would have differential effects on memory.

METHODS

Intracranial electrical stimulation was applied to the entorhinal area of twenty-two participants with already implanted electrodes as they completed visual memory tasks.

RESULTS

We found that stimulation of right entorhinal white matter during learning had a beneficial effect on subsequent memory, while stimulation of adjacent gray matter or left-sided stimulation was ineffective. This finding was consistent across three different visually guided memory tasks.

CONCLUSIONS

Our results highlight the importance of precise stimulation site on modulation of human hippocampal-dependent memory and suggest that stimulation of afferent input into the right hippocampus may be an especially promising target for enhancement of visual memory.

Ripples Have Distinct Spectral Properties and Phase-Amplitude Coupling With Slow Waves, but Indistinct Unit Firing, in Human Epileptogenic Hippocampus

Ripple oscillations (80-200 Hz) in the normal hippocampus are involved in memory consolidation during rest and sleep. In the epileptic brain, increased ripple and fast ripple (200-600 Hz) rates serve as a biomarker of epileptogenic brain. We report that both ripples and fast ripples exhibit a preferred phase angle of coupling with the trough-peak (or On-Off) state transition of the sleep slow wave in the hippocampal seizure onset zone (SOZ). Ripples on slow waves in the hippocampal SOZ also had a lower power, greater spectral frequency, and shorter duration than those in the non-SOZ. Slow waves in the mesial temporal lobe modulated the baseline firing rate of excitatory neurons, but did not significantly influence the increased firing rate associated with ripples. In summary, pathological ripples and fast ripples occur preferentially during the On-Off state transition of the slow wave in the epileptogenic hippocampus, and ripples do not require the increased recruitment of excitatory neurons.

Localizing epileptogenic regions using high-frequency oscillations and machine learning

Pathological high frequency oscillations (HFOs) are putative neurophysiological biomarkers of epileptogenic brain tissue. Utilizing HFOs for epilepsy surgery planning offers the promise of improved seizure outcomes for patients with medically refractory epilepsy. This review discusses possible machine learning strategies that can be applied to HFO biomarkers to better identify epileptogenic regions. We discuss the role of HFO rate, and utilizing features such as explicit HFO properties (spectral content, duration, and power) and phase-amplitude coupling for distinguishing pathological HFO (pHFO) events from physiological HFO events. In addition, the review highlights the importance of neuroanatomical localization in machine learning strategies.

Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding

BACKGROUND

We sought to determine if ripple oscillations (80-120 Hz), detected in intracranial electroencephalogram (iEEG) recordings of patients with epilepsy, correlate with an enhancement or disruption of verbal episodic memory encoding.

METHODS

We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the relationship between the occurrence of ripple and spike events during word presentation and the odds of successful word recall following a distractor epoch and included the seizure onset zone (SOZ) as a covariate in the LRMs.

RESULTS

We detected events during 58,312 word presentation trials from 7630 unique electrode sites. The probability of ripple on spike (RonS) events was increased in the SOZ (p < 0.04). In the left temporal neocortex, RonS events during word presentation corresponded with a decrease in the odds ratio (OR) of successful recall, however, this effect only met significance in the SOZ (OR of word recall: 0.71, 95% confidence interval (CI): 0.59-0.85, n = 158 events, adaptive Hochberg, p < 0.01). Ripple on oscillation (RonO) events that occurred in the left temporal neocortex non-SOZ also correlated with decreased odds of successful recall (OR: 0.52, 95% CI: 0.34-0.80, n = 140, adaptive Hochberg, p < 0.01). Spikes and RonS that occurred during word presentation in the left middle temporal gyrus (MTG) correlated with the most significant decrease in the odds of successful recall, irrespective of the location of the SOZ (adaptive Hochberg, p < 0.01).

CONCLUSION

Ripples and spikes generated in the left temporal neocortex are associated with impaired verbal episodic memory encoding. Although physiological and pathological ripple oscillations were not distinguished during cognitive tasks, our results show an association of undifferentiated ripples with impaired encoding. The effect was sometimes specific to regions outside the SOZ, suggesting that widespread effects of epilepsy outside the SOZ may contribute to cognitive impairment.

Low-voltage fast seizures in humans begin with increased interneuron firing

OBJECTIVE

Intracellular recordings from cells in entorhinal cortex tissue slices show that low-voltage fast (LVF) onset seizures are generated by inhibitory events. Here, we determined whether increased firing of interneurons occurs at the onset of spontaneous mesial-temporal LVF seizures recorded in patients.

METHODS

The seizure onset zone (SOZ) was identified using visual inspection of the intracranial electroencephalogram. We used wavelet clustering and temporal autocorrelations to characterize changes in single-unit activity during the onset of LVF seizures recorded from microelectrodes in mesial-temporal structures. Action potentials generated by principal neurons and interneurons (ie, putative excitatory and inhibitory neurons) were distinguished using waveform morphology and K-means clustering.

RESULTS

From a total of 200 implanted microelectrodes in 9 patients during 13 seizures, we isolated 202 single units; 140 (69.3%) of these units were located in the SOZ, and 40 (28.57%) of them were classified as inhibitory. The waveforms of both excitatory and inhibitory units remained stable during the LVF epoch (p > > 0.05). In the mesial-temporal SOZ, inhibitory interneurons increased their firing rate during LVF seizure onset (p < 0.01). Excitatory neuron firing rates peaked 10 seconds after the inhibitory neurons (p < 0.01). During LVF spread to the contralateral mesial temporal lobe, an increase in inhibitory neuron firing rate was also observed (p < 0.01).

INTERPRETATION

Our results suggest that seizure generation and spread during spontaneous mesial-temporal LVF onset events in humans may result from increased inhibitory neuron firing that spawns a subsequent increase in excitatory neuron firing and seizure evolution. Ann Neurol 2018;84:588-600.

Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively

OBJECTIVE

To develop and validate a detector that identifies ripple (80-200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ).

METHODS

iEEG recordings from 16 patients were first band-pass filtered (80-600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection.

RESULTS

The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p < .001).

CONCLUSIONS

Utilizing ICA to analyze iEEG recordings in referential montage provides many benefits to the study of high-frequency oscillations. The ripple rates and properties defined using this approach may accurately delineate the seizure onset zone.

SIGNIFICANCE

Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of HFO biomarkers.

A method for the topographical identification and quantification of high frequency oscillations in intracranial electroencephalography recordings

OBJECTIVE

To develop a reliable software method using a topographic analysis of time-frequency plots to distinguish ripple (80-200 Hz) oscillations that are often associated with EEG sharp waves or spikes (RonS) from sinusoid-like waveforms that appear as ripples but correspond with digital filtering of sharp transients contained in the wide bandwidth EEG.

METHODS

A custom algorithm distinguished true from false ripples in one second intracranial EEG (iEEG) recordings using wavelet convolution, identifying contours of isopower, and categorizing these contours into sets of open or closed loop groups. The spectral and temporal features of candidate groups were used to classify the ripple, and determine its duration, frequency, and power. Verification of detector accuracy was performed on the basis of simulations, and visual inspection of the original and band-pass filtered signals.

RESULTS

The detector could distinguish simulated true from false ripple on spikes (RonS). Among 2934 visually verified trials of iEEG recordings and spectrograms exhibiting RonS the accuracy of the detector was 88.5% with a sensitivity of 81.8% and a specificity of 95.2%. The precision was 94.5% and the negative predictive value was 84.0% (N = 12). Among, 1,370 trials of iEEG recording exhibiting RonS that were reviewed blindly without spectrograms the accuracy of the detector was 68.0%, with kappa equal to 0.01 ± 0.03. The detector successfully distinguished ripple from high spectral frequency 'fast ripple' oscillations (200-600 Hz), and characterize ripple duration and spectral frequency and power. The detector was confounded by brief bursts of gamma (30-80 Hz) activity in 7.31 ± 6.09% of trials, and in 30.2 ± 14.4% of the true RonS detections ripple duration was underestimated.

CONCLUSIONS

Characterizing the topographic features of a time-frequency plot generated by wavelet convolution is useful for distinguishing true oscillations from false oscillations generated by filter ringing.

SIGNIFICANCE

Categorizing ripple oscillations and characterizing their properties can improve the clinical utility of the biomarker.

Bimodal coupling of ripples and slower oscillations during sleep in patients with focal epilepsy

OBJECTIVE

Differentiating pathologic and physiologic high-frequency oscillations (HFOs) is challenging. In patients with focal epilepsy, HFOs occur during the transitional periods between the up and down state of slow waves. The preferred phase angles of this form of phase-event amplitude coupling are bimodally distributed, and the ripples (80-150 Hz) that occur during the up-down transition more often occur in the seizure-onset zone (SOZ). We investigated if bimodal ripple coupling was also evident for faster sleep oscillations, and could identify the SOZ.

METHODS

Using an automated ripple detector, we identified ripple events in 40-60 min intracranial electroencephalography (iEEG) recordings from 23 patients with medically refractory mesial temporal lobe or neocortical epilepsy. The detector quantified epochs of sleep oscillations and computed instantaneous phase. We utilized a ripple phasor transform, ripple-triggered averaging, and circular statistics to investigate phase event-amplitude coupling.

RESULTS

We found that at some individual recording sites, ripple event amplitude was coupled with the sleep oscillatory phase and the preferred phase angles exhibited two distinct clusters (p < 0.05). The distribution of the pooled mean preferred phase angle, defined by combining the means from each cluster at each individual recording site, also exhibited two distinct clusters (p < 0.05). Based on the range of preferred phase angles defined by these two clusters, we partitioned each ripple event at each recording site into two groups: depth iEEG peak-trough and trough-peak. The mean ripple rates of the two groups in the SOZ and non-SOZ (NSOZ) were compared. We found that in the frontal (spindle, p = 0.009; theta, p = 0.006, slow, p = 0.004) and parietal lobe (theta, p = 0.007, delta, p = 0.002, slow, p = 0.001) the SOZ incidence rate for the ripples occurring during the trough-peak transition was significantly increased.

SIGNIFICANCE

Phase-event amplitude coupling between ripples and sleep oscillations may be useful to distinguish pathologic and physiologic events in patients with frontal and parietal SOZ.

Ripples on spikes show increased phase-amplitude coupling in mesial temporal lobe epilepsy seizure-onset zones

OBJECTIVE

Ripples (80-150 Hz) recorded from clinical macroelectrodes have been shown to be an accurate biomarker of epileptogenic brain tissue. We investigated coupling between epileptiform spike phase and ripple amplitude to better understand the mechanisms that generate this type of pathologic ripple (pRipple) event.

METHODS

We quantified phase amplitude coupling (PAC) between epileptiform electroencephalography (EEG) spike phase and ripple amplitude recorded from intracranial depth macroelectrodes during episodes of sleep in 12 patients with mesial temporal lobe epilepsy. PAC was determined by (1) a phasor transform that corresponds to the strength and rate of ripples coupled with spikes, and a (2) ripple-triggered average to measure the strength, morphology, and spectral frequency of the modulating and modulated signals. Coupling strength was evaluated in relation to recording sites within and outside the seizure-onset zone (SOZ).

RESULTS

Both the phasor transform and ripple-triggered averaging methods showed that ripple amplitude was often robustly coupled with epileptiform EEG spike phase. Coupling was found more regularly inside than outside the SOZ, and coupling strength correlated with the likelihood a macroelectrode's location was within the SOZ (p < 0.01). The ratio of the rate of ripples coupled with EEG spikes inside the SOZ to rates of coupled ripples in non-SOZ was greater than the ratio of rates of ripples on spikes detected irrespective of coupling (p < 0.05). Coupling strength correlated with an increase in mean normalized ripple amplitude (p < 0.01), and a decrease in mean ripple spectral frequency (p < 0.05).

SIGNIFICANCE

Generation of low-frequency (80-150 Hz) pRipples in the SOZ involves coupling between epileptiform spike phase and ripple amplitude. The changes in excitability reflected as epileptiform spikes may also cause clusters of pathologically interconnected bursting neurons to grow and synchronize into aberrantly large neuronal assemblies.

Seizure localization using ictal phase-locked high gamma: A retrospective surgical outcome study

OBJECTIVE

To determine whether resection of areas with evidence of intense, synchronized neural firing during seizures is an accurate indicator of postoperative outcome.

METHODS

Channels meeting phase-locked high gamma (PLHG) criteria were identified retrospectively from intracranial EEG recordings (102 seizures, 46 implantations, 45 patients). Extent of removal of both the seizure onset zone (SOZ) and PLHG was correlated with seizure outcome, classified as good (Engel class I or II, n = 32) or poor (Engel class III or IV, n = 13).

RESULTS

Patients with good outcomes had significantly greater proportions of both SOZ and the first 4 (early) PLHG sites resected. Improved outcome classification was noted with early PLHG, as measured by the area under the receiver operating characteristic curves (PLHG 0.79, SOZ 0.68) and by odds ratios for resections including at least 75% of sites identified by each measure (PLHG 9.7 [95% CI: 2.3-41.5], SOZ 5.3 [95% CI: 1.2-23.3]). Among patients with resection of at least 75% of the SOZ, 78% (n = 30) had good outcomes, increasing to 91% when the resection also included at least 75% of early PLHG sites (n = 22).

CONCLUSIONS

This study demonstrates the localizing value of early PLHG, which is comparable to that provided by the SOZ. Incorporation of PLHG into the clinical evaluation may improve surgical efficacy and help to focus resections on the most critical areas.

Field effects and ictal synchronization: insights from in homine observations

It has been well established in animal models that electrical fields generated during inter-ictal and ictal discharges are strong enough in intensity to influence action potential firing threshold and synchronization. We discuss recently published data from microelectrode array recordings of human neocortical seizures and speculate about the possible role of field effects in neuronal synchronization. We have identified two distinct seizure territories that cannot be easily distinguished by traditional EEG analysis. The ictal core exhibits synchronized neuronal burst firing, while the surrounding ictal penumbra exhibits asynchronous and relatively sparse neuronal activity. In the ictal core large amplitude rhythmic ictal discharges produce large electric fields that correspond with highly synchronous neuronal firing. In the penumbra rhythmic ictal discharges are smaller in amplitude, but large enough to influence spike timing, yet neuronal synchrony is not observed. These in homine observations are in accord with decades of animal studies supporting a role of field effects in neuronal synchronization during seizures, yet also highlight how field effects may be negated in the presence of strong synaptic inhibition in the penumbra.

Ictal high frequency oscillations distinguish two types of seizure territories in humans

High frequency oscillations have been proposed as a clinically useful biomarker of seizure generating sites. We used a unique set of human microelectrode array recordings (four patients, 10 seizures), in which propagating seizure wavefronts could be readily identified, to investigate the basis of ictal high frequency activity at the cortical (subdural) surface. Sustained, repetitive transient increases in high gamma (80-150 Hz) amplitude, phase-locked to the low-frequency (1-25 Hz) ictal rhythm, correlated with strong multi-unit firing bursts synchronized across the core territory of the seizure. These repetitive high frequency oscillations were seen in recordings from subdural electrodes adjacent to the microelectrode array several seconds after seizure onset, following ictal wavefront passage. Conversely, microelectrode recordings demonstrating only low-level, heterogeneous neural firing correlated with a lack of high frequency oscillations in adjacent subdural recording sites, despite the presence of a strong low-frequency signature. Previously, we reported that this pattern indicates a failure of the seizure to invade the area, because of a feedforward inhibitory veto mechanism. Because multi-unit firing rate and high gamma amplitude are closely related, high frequency oscillations can be used as a surrogate marker to distinguish the core seizure territory from the surrounding penumbra. We developed an efficient measure to detect delayed-onset, sustained ictal high frequency oscillations based on cross-frequency coupling between high gamma amplitude and the low-frequency (1-25 Hz) ictal rhythm. When applied to the broader subdural recording, this measure consistently predicted the timing or failure of ictal invasion, and revealed a surprisingly small and slowly spreading seizure core surrounded by a far larger penumbral territory. Our findings thus establish an underlying neural mechanism for delayed-onset, sustained ictal high frequency oscillations, and provide a practical, efficient method for using them to identify the small ictal core regions. Our observations suggest that it may be possible to reduce substantially the extent of cortical resections in epilepsy surgery procedures without compromising seizure control.

Intra- and inter-frequency brain network structure in health and schizophrenia

Empirical studies over the past two decades have provided support for the hypothesis that schizophrenia is characterized by altered connectivity patterns in functional brain networks. These alterations have been proposed as genetically mediated diagnostic biomarkers and are thought to underlie altered cognitive functions such as working memory. However, the nature of this dysconnectivity remains far from understood. In this study, we perform an extensive analysis of functional connectivity patterns extracted from MEG data in 14 subjects with schizophrenia and 14 healthy controls during a 2-back working memory task. We investigate uni-, bi- and multivariate properties of sensor time series by computing wavelet entropy of and correlation between time series, and by constructing binary networks of functional connectivity both within and between classical frequency bands ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]). Networks are based on the mutual information between wavelet time series, and estimated for each trial window separately, enabling us to consider both network topology and network dynamics. We observed significant decreases in time series entropy and significant increases in functional connectivity in the schizophrenia group in comparison to the healthy controls and identified an inverse relationship between these measures across both subjects and sensors that varied over frequency bands and was more pronounced in controls than in patients. The topological organization of connectivity was altered in schizophrenia specifically in high frequency [Formula: see text] and [Formula: see text] band networks as well as in the [Formula: see text]-[Formula: see text] cross-frequency networks. Network topology varied over trials to a greater extent in patients than in controls, suggesting disease-associated alterations in dynamic network properties of brain function. Our results identify signatures of aberrant neurophysiological behavior in schizophrenia across uni-, bi- and multivariate scales and lay the groundwork for further clinical studies that might lead to the discovery of new intermediate phenotypes.

Field effects in the CNS play functional roles

An endogenous electrical field effect, i.e., ephaptic transmission, occurs when an electric field associated with activity occurring in one neuron polarizes the membrane of another neuron. It is well established that field effects occur during pathological conditions, such as epilepsy, but less clear if they play a functional role in the healthy brain. Here, we describe the principles of field effect interactions, discuss identified field effects in diverse brain structures from the teleost Mauthner cell to the mammalian cortex, and speculate on the function of these interactions. Recent evidence supports that relatively weak endogenous and exogenous field effects in laminar structures reach significance because they are amplified by network interactions. Such interactions may be important in rhythmogenesis for the cortical slow wave and hippocampal sharp wave-ripple, and also during transcranial stimulation.

Correlation of C-start behaviors with neural activity recorded from the hindbrain in free-swimming goldfish (Carassius auratus)

Startle behaviors in teleost fishes are well suited for investigations of mechanisms of sensorimotor integration because the behavior is quantifiable and much of the underlying circuitry has been identified. The teleost C-start is triggered by an action potential in one of the two Mauthner (M) cells. To correlate C-start behavior with electrophysiology, extracellular recordings were obtained from the surface of the medulla oblongata in the hindbrain,close to the M-axons, in freely swimming goldfish monitored using high-speed video. The recordings included action potentials generated by the two M-axons,as well as neighboring axons in the dorsal medial longitudinal fasciculus. Axonal backfills indicated that the latter originate from identifiable reticulospinal somata in rhombomeres 2-8 and local interneurons. Diverse auditory and visual stimuli evoked behaviors with kinematics characteristic of the C-start, and the amplitude of the first component of the hindbrain field potential correlated with the C-start direction. The onset of the field potential preceded that of the simultaneously recorded trunk EMG and movement initiation by 1.08±0.04 and 8.13±0.17 ms, respectively. A subsequent longer latency field potential was predictive of a counterturn. These results indicate that characteristic features of the C-start can be extracted from the neural activity of the M-cell and a population of other reticulospinal neurons in free-swimming goldfish.

Neural representation of object approach in a decision-making motor circuit

Although behavior is ultimately guided by decision-making neurons and their associated networks, the mechanisms underlying neural decision-making in a behaviorally relevant context remain mostly elusive. To address this question, we analyzed goldfish escapes in response to distinct visual looming stimuli with high-speed video and compared them with electrophysiological responses of the Mauthner cell (M-cell), the threshold detector that initiates such behaviors. These looming stimuli evoke powerful and fast body-bend (C-start) escapes with response probabilities between 0.7 and 0.91 and mean latencies ranging from 142 to 716 ms. Chronic recordings showed that these C-starts are correlated with M-cell activity. Analysis of response latency as a function of the different optical parameters characterizing the stimuli suggests response threshold is closely correlated to a dynamically scaled function of angular retinal image size, (t), specifically kappa(t) = (t-delta x e(-beta(t-delta)), where the exponential term progressively reduces the weight of (t). Intracellular recordings show that looming stimuli typically evoked bursts of graded EPSPs with peak amplitudes up to 9 mV in the M-cell. The proposed scaling function kappa(t) predicts the slope of the depolarizing envelope of these EPSPs and the timing of the largest peak. An analysis of the firing rate of presynaptic inhibitory interneurons suggests the timing of the EPSP peak is shaped by an interaction of excitatory and inhibitory inputs to the M-cell and corresponds to the temporal window in which the probabilistic decision of whether or not to escape is reached.

Representation of auditory signals in the M-cell: role of electrical synapses

The teleost Mauthner (M-) cell mediates a sound-evoked escape behavior. A major component of the auditory input is transmitted by large myelinated club endings of the posterior VIIIth nerve. Paradoxically, although nerve stimulations revealed these afferents have mixed electrical and glutamatergic synapses on the M-cell's distal lateral dendrite, paired pre- and postsynaptic recordings indicated most individual connections are chemically silent. To determine the sensory information encoded and the relative contributions of these two transmission modes, M-cell responses to acoustic stimuli in air were recorded intracellularly. Excitatory postsynaptic potentials (EPSPs) evoked by both short 100- to 900-Hz "pips" and longer-lasting amplitude- and frequency-modulated sounds were dominated by fast, repetitive EPSPs superimposed on an underlying slow depolarization. Fast EPSPs 1) have kinetics comparable to presynaptic action potentials, 2) are maximal on the distal lateral dendrite, and 3) are insensitive to GluR antagonists. They presumably are coupling potentials, and power spectral analysis indicated they constitute a high-pass signal that accurately tracks sound frequency and amplitude. The spatial profile of the slow EPSP suggests both proximal and distal dendritic sources, a result supported by predictions of a multicompartmental model and the effects of AMPAR antagonists, which preferentially reduced the proximal component. Thus a second class of afferents generates a portion of the slow EPSP that, with sound stimuli, demonstrate that the dominant mode of transmission at LMCE synapses is electrical. The slow EPSP is a dynamic, low-pass representation of stimulus strength. Accordingly, amplitude and phase information, which are segregated in other systems, are faithfully represented in the M-cell.

Rat navigation guided by remote control

Free animals can be 'virtually' trained by microstimulating key areas of their brains.

Baculovirus-mediated large-scale expression and purification of a polyhistidine-tagged rubella virus capsid protein

The capsid protein of rubella virus was produced in baculovirus-infected Spodoptera frugiperda insect cells, with a polyhistidine affinity tag at the carboxy terminus. The RV capsid recombinant protein was produced in a 10-liter bioreactor and purified, under nondenaturing conditions, using immobilized metal-ion affinity chromatography. Immunoblot analyses indicated that the purified recombinant protein was intact and migrated with the expected molecular weight. The final yield was 5 mg of purified protein per liter of cell culture. Surface plasmon resonance was used to investigate the antigenic potential of the histidine tagged capsid protein in an antigen-antibody interaction study. A specific interaction between the two proteins was shown. Our results suggest that this strategy should be useful in interaction studies of other virus-specific proteins and antibodies.

Synthesis of soluble rubella virus spike proteins in two lepidopteran insect cell lines: large scale production of the E1 protein

The two envelope glycoproteins of rubella virus (RV), E1 of 58 kDa and E2 of 42-47 kDa, were individually expressed in lepidopteran Spodoptera frugiperda as well as in Trichoplusia ni insect cells using baculovirus vectors. The authentic signal sequences of E1 and E2 were replaced with the honeybee melittin signal sequence, allowing efficient entrance into the secretory pathway of the insect cell. In addition, the hydrophobic transmembrane anchors at the carboxyl termini of E1 and E2 proteins were removed to enable secretion rather than maintenance in the cellular membranes. Synthesis of the recombinant proteins in the absence and presence of tunicamycin revealed that both E1 and E2 were glycosylated with apparent molecular weights of 52 kDa and 37 kDa, respectively. Recombinant E2 appeared to be partially secreted, whereas E1 was essentially found inside the infected insect cell. The E1 protein was produced in large scale using a 10-1 bioreactor and serum-free medium (SFM). Purification of the recombinant protein product was performed from cytoplasmic extracts by ammonium sulphate precipitation followed by Concanavalin A affinity chromatography. This type of purified recombinant viral glycoproteins may be useful not only in diagnostic medicine or for immunization, but should enable studies designed to solve the structure of the virus particle.

Phantom limb pain and etiology of amputation in unilateral lower extremity amputees

The relationships between phantom limb pain and both the etiology of amputation (blood clots, nonclot diabetes, and miscellaneous) and the occurrence of gangrene and/or infection were investigated in 92 unilateral lower extremity (LE) amputees who were seen sequentially. There were 55 above-knee (AK) and 37 below-knee (BK) amputations in 61 men and 31 women. The mean age was 51.4 years. The blood-clot etiology had the highest levels of phantom pain both pre- and postrehabilitation, the longest time interval between amputation and prosthetic fitting, and the greatest number of medical conditions. The nonclot diabetes and miscellaneous etiologies followed in order. A history of gangrene and/or infection was associated with higher levels of pain and longer time interval between amputation and prosthetic fitting.

Carpal tunnel syndrome: a clinicopathologic study

We evaluated 44 patients with carpal tunnel syndrome and performed histological evaluations of tenosynovium taken at the time of carpal tunnel release. Age, disease and work history, radiographs, and outcome were assessed. The clinical parameters were then compared with the histologic features to determine if the histology was predictive of the clinical course of carpal tunnel syndrome. We found no significance in the histologic changes in patients with carpal tunnel syndrome when age, duration of symptoms, work history, radiographs, and outcome were evaluated.

Preoperative radiation therapy and iododeoxyuridine for large retroperitoneal sarcomas

PURPOSE

Local failure is frequent after conventional therapy for patients with retroperitoneal sarcomas. A Phase I/II multimodality approach was used, combining iododeoxyuridine (IdUrd) and radiation therapy, followed by attempted surgical resection, with the goal of improving local control.

METHODS AND MATERIALS

Patients with retroperitoneal sarcomas were treated with three to five consecutive cycles of treatment. Each 14-day cycle consisted of a continuous intravenous infusion of IdUrd on days 1-5, twice a day radiation therapy (1.25 Gy/fraction) on days 8-12, and a break on day 13 and 14. Surgical resection was attempted after three or five cycles. Patients resected after three cycles received an additional two cycles of treatment with radiation directed to the tumor bed. IdUrd dose was escalated in Phase I fashion (1000 mg/m2/day, 1333 mg/m2/day, and 1600 mg/m2/day). The median potential follow-up was 31 months.

RESULTS

Sixteen patients (13 with high grade tumors) were treated. The median maximum tumor size was 17 cm. Resection margins were negative in four patients, microscopically positive in four patients, and grossly positive in three patients. Five patients were not resected. The only grade 4 acute toxicity observed was vomiting which occurred in three patients receiving upper abdominal radiation. Postsurgical and long-term complications were rare. Median survival overall and for resected patients were 18 and 32 months, respectively. Local control was observed in three out of four patients with negative margins (9, 40+, and 51+ months), two out of four patients with microscopically positive margins (4 and 22 months), and one out of three patients with grossly positive margins (46+ months). The overall freedom from local progression was 45% at 24 months.

CONCLUSION

Retroperitoneal sarcomas can be resected after preoperative radiation therapy and IdUrd, with encouraging local control in patients resected with negative or microscopically positive margins. The recommended dose using this drug and radiation schedule appears to be 1600 mg/m2/day, which will form the basis for a Phase II trial.

Large-scale propagation of insect cells

Cultured insect cells have many uses in agriculture and medicine. They can be used in the diagnosis and isolation of a number of viruses infecting both animals and plants and for the laboratory study of these viruses. Large-volume culture of insect cells has been envisioned as a way of producing viruses for use in controlling insect pests and for the production of viral antigens for vaccine preparations. Recently they have become a potentially valuable way of producing a variety of proteins for human and veterinary medicine using the genetically engineered baculovirus expression vectors. The development of satisfactory cell lines and culture methods has proceeded at a slow, irregular pace, inhibited by the lack of knowledge of the physiology of the insect, its small size, and often by the lack of consistent, adequate support for the necessary developmental research. However, now that the basic culture systems are available, cell lines have been developed or can easily be developed for most needs. Suitable media are available and recent developments in refining existing media formations have resulted in low-cost media containing little protein to interfere with down-stream processing of cellular metabolites. Future developments are likely to further improve the media formulations and lower the cost. Technical problems relating to oxygen demand and cell fragility that inhibited the continued development of large-volume culture systems beyond the laboratory a few years ago now appear to be solved or at least are solvable. The successful culture of the Spodoptera cells in bioreactors of 40-liter capacity indicates that means of producing insect cells or their metabolic products on a commercial scale can be made economically feasible.

Herpesvirus simiae (B virus): replication of the virus and identification of viral polypeptides in infected cells

The events and products of replication of Herpesvirus simiae (B virus) in Vero cells were studied. The time course of the synthetic events of DNA replication and protein synthesis were found to be similar to the processes of the herpes simplex viruses and SA 8. Infectious progeny virus were detected by 4 hours post infection and were first found extracellularly between 6 and 8 hours post infection (PI). As in the case of SA 8, all cell lines tested were permissive for lytic infection by B virus. Analyses of B virus-infected cells by SDS-polyacrylamide gel electrophoresis (SDS-PAGE) revealed approximately 50 infected cell polypeptides (ICP) ranging in molecular weight from about 26,000 to 239,000 daltons. The kinetics of synthesis of the ICPs were also identified. At least nine glucosamine-containing glycopeptides were noted ranging from 133,000 to 29,000 daltons.

Effect of aluminum chloride and zinc sulfate on Autographa california nuclear polyhedrosis virus (ACNPV) replication in cell culture

When IPL-SF-21AE III continuous insect cell line was grown and maintained in IPL-41 insect cell culture medium supplemented with 16 microM of AlCl3 or 0.24 microM of ZnSO4 . 7H2O, or both metallic salts, and then infected with Autographa california nuclear polyhedrosis virus, virus replication was increased significantly. The yield of polyhedral inclusion bodies (PIB) was enhanced up to 121%. Synthesis of cell-free nonoccluded virus was increased to 365% when infectivity was assayed by the plaque method. Newly applied electron microscopic quantitation and stereological techniques also revealed a significant increase in virus particles (VP) and in amount and size of PIB as well as number of VP per PIB.