Nationwide evaluation of quality and composition of colostrum on dairy farms in the United States

The objective of this study was to characterize the quality of maternal colostrum (MC) fed to newborn dairy calves in the United States and identify the proportion of MC that meets industry standards for IgG concentration and total plate count (TPC). Samples of MC (n=827) were collected from 67 farms in 12 states between June and October 2010. Samples were collected from Holsteins (n=494), Jerseys (n=87), crossbred (n=7), and unidentified dairy cattle (n=239) from first (n=49), second (n=174), third or greater (n=128), and unknown (n=476) lactations. Samples were identified as fresh (n=196), refrigerated (n=152), or frozen (n=479) before collection, as well as whether the sample was from an individual cow (n=734) or pooled (n=93). Concentration of IgG in MC ranged from <1 to 200mg/mL, with a mean IgG concentration of 68.8 mg/mL (SD=32.8). Almost 30% of MC contained <50 mg of IgG/mL. The IgG concentration increased with parity (42.4, 68.6, and 95.9 mg/mL in first, second, and third and later lactations, respectively). No differences in IgG concentration were observed among breeds or storage method; however, IgG was highest in samples collected in the Midwest and lowest in samples collected in the Southwest (79.7 vs. 64.3 mg/mL). Total plate count of samples ranged from 3.0 to 6.8 log(10) cfu/mL, with a mean of 4.9 log(10) cfu/mL (SD=0.9) and was greater in samples collected in the Southeast compared with other regions of the country. Pooled samples had greater TPC than individual samples and refrigerated samples had greater TPC than frozen and fresh samples. Almost 43% of samples collected had TPC >100,000 cfu/mL, 16.9% of the samples had >1 million cfu/mL. Only 39.4% of the samples collected met industry recommendations for both IgG concentration and TPC. Almost 60% of MC on dairy farms is inadequate, and a large number of calves are at risk of failure of passive transfer or bacterial infections, or both. Also, the data indicate that regional differences exist in colostrum quality.

Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings

There exist significant clinical and basic research needs for accurate, automated seizure detection algorithms. These algorithms have translational potential in responsive neurostimulation devices and in automatic parsing of continuous intracranial electroencephalography data. An important barrier to developing accurate, validated algorithms for seizure detection is limited access to high-quality, expertly annotated seizure data from prolonged recordings. To overcome this, we hosted a kaggle.com competition to crowdsource the development of seizure detection algorithms using intracranial electroencephalography from canines and humans with epilepsy. The top three performing algorithms from the contest were then validated on out-of-sample patient data including standard clinical data and continuous ambulatory human data obtained over several years using the implantable NeuroVista seizure advisory system. Two hundred teams of data scientists from all over the world participated in the kaggle.com competition. The top performing teams submitted highly accurate algorithms with consistent performance in the out-of-sample validation study. The performance of these seizure detection algorithms, achieved using freely available code and data, sets a new reproducible benchmark for personalized seizure detection. We have also shared a 'plug and play' pipeline to allow other researchers to easily use these algorithms on their own datasets. The success of this competition demonstrates how sharing code and high quality data results in the creation of powerful translational tools with significant potential to impact patient care.

Virtual resection predicts surgical outcome for drug-resistant epilepsy

Patients with drug-resistant epilepsy often require surgery to become seizure-free. While laser ablation and implantable stimulation devices have lowered the morbidity of these procedures, seizure-free rates have not dramatically improved, particularly for patients without focal lesions. This is in part because it is often unclear where to intervene in these cases. To address this clinical need, several research groups have published methods to map epileptic networks but applying them to improve patient care remains a challenge. In this study we advance clinical translation of these methods by: (i) presenting and sharing a robust pipeline to rigorously quantify the boundaries of the resection zone and determining which intracranial EEG electrodes lie within it; (ii) validating a brain network model on a retrospective cohort of 28 patients with drug-resistant epilepsy implanted with intracranial electrodes prior to surgical resection; and (iii) sharing all neuroimaging, annotated electrophysiology, and clinical metadata to facilitate future collaboration. Our network methods accurately forecast whether patients are likely to benefit from surgical intervention based on synchronizability of intracranial EEG (area under the receiver operating characteristic curve of 0.89) and provide novel information that traditional electrographic features do not. We further report that removing synchronizing brain regions is associated with improved clinical outcome, and postulate that sparing desynchronizing regions may further be beneficial. Our findings suggest that data-driven network-based methods can identify patients likely to benefit from resective or ablative therapy, and perhaps prevent invasive interventions in those unlikely to do so.

The efficacy of radiotherapy as postoperative treatment for desmoid tumors

PURPOSE

The purpose of this study was to determine if radiotherapy is a beneficial adjuvant treatment after desmoid tumor resection.

METHODS AND MATERIALS

A retrospective analysis was performed on 54 patients who underwent surgery without prior radiation at our institution between 1982 and 1998 to remove a desmoid tumor. Thirty-five patients had adjuvant radiation therapy after surgery, and 19 patients had surgery alone without immediate postoperative radiation. Sixteen of the 35 patients who underwent immediate postoperative radiation treatment had at least one prior resection before reoperation at our institution. Recurrence was defined as radiographic increase in tumor size after treatment. Follow-up interval (mean 39 months) and duration of local control were measured from the date of surgery at our institution. Potential prognostic factors for time to tumor progression were analyzed.

RESULTS

Adjuvant treatment with radiation was the only significant prognostic factor for local control. The five-year actuarial local control rate was 81% for the 35 patients who underwent radiation in addition to surgery, compared to 53% for the 19 patients who underwent surgery alone (p = 0.018). For the patients who did not receive adjuvant radiation, only younger age at the time of surgery was associated with increased risk of failure (p = 0.035). Gross or microscopic margin status and number of prior operations were not detected as prognostic for local failure. For patients who did receive postoperative radiation, only abdominal location was associated with increased risk of failure (p = 0.0097).

CONCLUSION

Radiation treatment as an adjuvant to surgery improved local control over surgery alone. Multiple operations before adjuvant radiation did not decrease the probability of subsequent tumor control. Radiation should be considered as adjuvant therapy to surgery if repeated surgery for a recurrent tumor would be complicated by a significant risk of morbidity.

Spatial distribution of interictal spikes fluctuates over time and localizes seizure onset

The location of interictal spikes is used to aid surgical planning in patients with medically refractory epilepsy; however, their spatial and temporal dynamics are poorly understood. In this study, we analysed the spatial distribution of interictal spikes over time in 20 adult and paediatric patients (12 females, mean age = 34.5 years, range = 5-58) who underwent intracranial EEG evaluation for epilepsy surgery. Interictal spikes were detected in the 24 h surrounding each seizure and spikes were clustered based on spatial location. The temporal dynamics of spike spatial distribution were calculated for each patient and the effects of sleep and seizures on these dynamics were evaluated. Finally, spike location was assessed in relation to seizure onset location. We found that spike spatial distribution fluctuated significantly over time in 14/20 patients (with a significant aggregate effect across patients, Fisher's method: P < 0.001). A median of 12 sequential hours were required to capture 80% of the variability in spike spatial distribution. Sleep and postictal state affected the spike spatial distribution in 8/20 and 4/20 patients, respectively, with a significant aggregate effect (Fisher's method: P < 0.001 for each). There was no evidence of pre-ictal change in the spike spatial distribution for any patient or in aggregate (Fisher's method: P = 0.99). The electrode with the highest spike frequency and the electrode with the largest area of downstream spike propagation both localized the seizure onset zone better than predicted by chance (Wilcoxon signed-rank test: P = 0.005 and P = 0.002, respectively). In conclusion, spikes localize seizure onset. However, temporal fluctuations in spike spatial distribution, particularly in relation to sleep and post-ictal state, can confound localization. An adequate duration of intracranial recording-ideally at least 12 sequential hours-capturing both sleep and wakefulness should be obtained to sufficiently sample the interictal network.

Determination of molecular-weight distribution of chitosan by high-performance liquid chromatography

Optimal conditions for using high-performance liquid chromatography (HPLC) in the size exclusion mode have been determined for measuring the molecular-weight (MW) distribution of chitosan samples. Physical separation according to molecular size was accomplished on the stationary phase of glass supports having controlled pore sizes ranging from 2500 to 40 A. Selection of column combinations was based on the requirements to resolve the higher MW fraction of chitosan and to give a linear calibration curve within the required MW range. The best combination of glass pore sizes and column lengths in two foot sections joined sequentially was: 2500 A (2 ft.), 1500 A (4 ft.), 550 A (6 ft.), 250 A (2 ft), 100 A (2 ft.), and 40 A (2 ft.). A loading study showed that an injection load of 500 mug, i.e. 100 mul at 5 g/l or 50 mul at 10 g/l (w/v), was the optimal load to give reproducible elution volumes, precision in quantitation, and minimum viscosity effects. The best calibration curve using defined dextran standards was obtained from the geometric mean of Mw (weight average MW) and Mn (number average MW) values and peak elution volumes. Precision in determining MW distribution of chitosan as well as dextran standards was better than 5% relative standard deviation, and the differences between these results and the manufacturer's data on the dextran standards were 6 to -17%. The MW distribution of a selected chitosan samples in 2% acetic acid thus determined was Mw = 2,055,000, Mn = 936,000, dispersity = 2.16, and the most abundant species was around 1,103,000. Analysis time for the HPLC separation was less than 20 min per sample. Chitosan is an effective coagulating agent for the treatment of food processing wastes and activated sludge from biological treatment systems. It is manufactured from chitin in shrimp and crab wastes. The rapid methods developed here for determining the MW distribution of chitosan preparations will be used to optimize the manufacturing process and guide the selection of more effective chitosan products.

Normative intracranial EEG maps epileptogenic tissues in focal epilepsy

Planning surgery for patients with medically refractory epilepsy often requires recording seizures using intracranial EEG. Quantitative measures derived from interictal intracranial EEG yield potentially appealing biomarkers to guide these surgical procedures; however, their utility is limited by the sparsity of electrode implantation as well as the normal confounds of spatiotemporally varying neural activity and connectivity. We propose that comparing intracranial EEG recordings to a normative atlas of intracranial EEG activity and connectivity can reliably map abnormal regions, identify targets for invasive treatment and increase our understanding of human epilepsy. Merging data from the Penn Epilepsy Center and a public database from the Montreal Neurological Institute, we aggregated interictal intracranial EEG retrospectively across 166 subjects comprising >5000 channels. For each channel, we calculated the normalized spectral power and coherence in each canonical frequency band. We constructed an intracranial EEG atlas by mapping the distribution of each feature across the brain and tested the atlas against data from novel patients by generating a z-score for each channel. We demonstrate that for seizure onset zones within the mesial temporal lobe, measures of connectivity abnormality provide greater distinguishing value than univariate measures of abnormal neural activity. We also find that patients with a longer diagnosis of epilepsy have greater abnormalities in connectivity. By integrating measures of both single-channel activity and inter-regional functional connectivity, we find a better accuracy in predicting the seizure onset zones versus normal brain (area under the curve = 0.77) compared with either group of features alone. We propose that aggregating normative intracranial EEG data across epilepsy centres into a normative atlas provides a rigorous, quantitative method to map epileptic networks and guide invasive therapy. We publicly share our data, infrastructure and methods, and propose an international framework for leveraging big data in surgical planning for refractory epilepsy.

Timing of once-a-day theophylline dose to match peak blood level with diurnal variation in severity of asthma

To test the hypothesis that nighttime and early morning signs and symptoms of air flow obstruction in patients with moderately severe asthma would be better controlled by theophylline given on a once-a-day evening dosing schedule chosen to provide a peak blood level in the early morning than by the traditional twice-a-day dosing schedule designed to maintain levels more constant throughout the 24-hour period, the effects on nocturnal asthma of Uniphyl once a day and Theo-Dur twice a day were studied in 14 patients with moderately severe asthma. Although both regimens were effective, more patients preferred the Uniphyl dosing schedule. Nighttime symptoms were better controlled, without an increase in daytime symptoms or significant side effects. Optimal timing of theophylline dosing is an important consideration in the management of asthma.

The Anatomical and Electrophysiological Subthalamic Nucleus Visualized by 3-T Magnetic Resonance Imaging

BACKGROUND:

Accurate localization of the subthalamic nucleus (STN) is critical to the success of deep brain stimulation surgery for Parkinson disease. Recent developments in high-field-strength magnetic resonance imaging (MRI) have made it possible to visualize the STN in greater detail. However, the relationship of the MR-visualized STN to the anatomic, electrophysiological, or atlas-predicted STN remains controversial.

OBJECTIVE:

To evaluate the size of the STN visualized on 3-T MRI compared with anatomic measurements in cadaver studies and to compare the predictions of 3-T MRI and those of the Schaltenbrand-Wahren (SW) atlas for intraoperative STN microelectrode recordings.

METHODS:

We evaluated the STN by 3-T MRI and intraoperative microelectrode recordings in 20 Parkinson disease patients undergoing deep brain stimulation surgery. We compared our findings with anatomic cadaver studies and with the individually scaled SW atlas-based predictions for each patient.

RESULTS:

The dimensions of the 3-T MR-visualized STN were very similar to those of the largest anatomic study (MRI length, width, and height: 9.8 ± 1.6, 11.5 ± 1.6, and 3.7 ± 0.7 mm, respectively; n = 40; cadaver length, width, and height: 9.3 ± 0.7, 10.6 ± 0.9, and 3.1 ± 0.5 mm, respectively; n = 100). The amount of STN traversed during intraoperative microelectrode recordings was better correlated to the 3-T MR-visualized STN than the SW atlas-predicted STN (R = 0.38 vs R = −0.17).

CONCLUSION:

The STN as visualized on 3-T MRI corresponds well with cadaveric anatomic studies and intraoperative electrophysiology. STN visualization with 3-T MRI may be an improvement over SW atlas-based localization for STN deep brain stimulation surgery in Parkinson disease.

OUP accepted manuscript

Objective

Materials and Methods

Results

Discussion and Conclusion

Spike patterns surrounding sleep and seizures localize the seizure-onset zone in focal epilepsy

OBJECTIVE

Interictal spikes help localize seizure generators as part of surgical planning for drug-resistant epilepsy. However, there are often multiple spike populations whose frequencies change over time, influenced by brain state. Understanding state changes in spike rates will improve our ability to use spikes for surgical planning. Our goal was to determine the effect of sleep and seizures on interictal spikes, and to use sleep and seizure-related changes in spikes to localize the seizure-onset zone (SOZ).

METHODS

We performed a retrospective analysis of intracranial electroencephalography (EEG) data from patients with focal epilepsy. We automatically detected interictal spikes and we classified different time periods as awake or asleep based on the ratio of alpha to delta power, with a secondary analysis using the recently published SleepSEEG algorithm. We analyzed spike rates surrounding sleep and seizures. We developed a model to localize the SOZ using state-dependent spike rates.

RESULTS

We analyzed data from 101 patients (54 women, age range 16-69). The normalized alpha-delta power ratio accurately classified wake from sleep periods (area under the curve = .90). Spikes were more frequent in sleep than wakefulness and in the post-ictal compared to the pre-ictal state. Patients with temporal lobe epilepsy had a greater wake-to-sleep and pre- to post-ictal spike rate increase compared to patients with extra-temporal epilepsy. A machine-learning classifier incorporating state-dependent spike rates accurately identified the SOZ (area under the curve = .83). Spike rates tended to be higher and better localize the seizure-onset zone in non-rapid eye movement (NREM) sleep than in wake or REM sleep.

SIGNIFICANCE

The change in spike rates surrounding sleep and seizures differs between temporal and extra-temporal lobe epilepsy. Spikes are more frequent and better localize the SOZ in sleep, particularly in NREM sleep. Quantitative analysis of spikes may provide useful ancillary data to localize the SOZ and improve surgical planning.

The sensitivity of network statistics to incomplete electrode sampling on intracranial EEG

Network neuroscience applied to epilepsy holds promise to map pathological networks, localize seizure generators, and inform targeted interventions to control seizures. However, incomplete sampling of the epileptic brain because of sparse placement of intracranial electrodes may affect model results. In this study, we evaluate the sensitivity of several published network measures to incomplete spatial sampling and propose an algorithm using network subsampling to determine confidence in model results. We retrospectively evaluated intracranial EEG data from 28 patients implanted with grid, strip, and depth electrodes during evaluation for epilepsy surgery. We recalculated global and local network metrics after randomly and systematically removing subsets of intracranial EEG electrode contacts. We found that sensitivity to incomplete sampling varied significantly across network metrics. This sensitivity was largely independent of whether seizure onset zone contacts were targeted or spared from removal. We present an algorithm using random subsampling to compute patient-specific confidence intervals for network localizations. Our findings highlight the difference in robustness between commonly used network metrics and provide tools to assess confidence in intracranial network localization. We present these techniques as an important step toward translating personalized network models of seizures into rigorous, quantitative approaches to invasive therapy.

Long-term epilepsy outcome dynamics revealed by natural language processing of clinic notes

OBJECTIVE

Electronic medical records allow for retrospective clinical research with large patient cohorts. However, epilepsy outcomes are often contained in free text notes that are difficult to mine. We recently developed and validated novel natural language processing (NLP) algorithms to automatically extract key epilepsy outcome measures from clinic notes. In this study, we assessed the feasibility of extracting these measures to study the natural history of epilepsy at our center.

METHODS

We applied our previously validated NLP algorithms to extract seizure freedom, seizure frequency, and date of most recent seizure from outpatient visits at our epilepsy center from 2010 to 2022. We examined the dynamics of seizure outcomes over time using Markov model-based probability and Kaplan-Meier analyses.

RESULTS

Performance of our algorithms on classifying seizure freedom was comparable to that of human reviewers (algorithm F1 = .88 vs. human annotatorκ = .86). We extracted seizure outcome data from 55 630 clinic notes from 9510 unique patients written by 53 unique authors. Of these, 30% were classified as seizure-free since the last visit, 48% of non-seizure-free visits contained a quantifiable seizure frequency, and 47% of all visits contained the date of most recent seizure occurrence. Among patients with at least five visits, the probabilities of seizure freedom at the next visit ranged from 12% to 80% in patients having seizures or seizure-free at the prior three visits, respectively. Only 25% of patients who were seizure-free for 6 months remained seizure-free after 10 years.

SIGNIFICANCE

Our findings demonstrate that epilepsy outcome measures can be extracted accurately from unstructured clinical note text using NLP. At our tertiary center, the disease course often followed a remitting and relapsing pattern. This method represents a powerful new tool for clinical research with many potential uses and extensions to other clinical questions.

Attitudes Toward Cognitive Enhancement: The Role of Metaphor and Context

The widespread use of stimulants among healthy individuals to improve cognition has received growing attention; however, public attitudes toward this practice are not well understood. We determined the effect of framing metaphors and context of use on public opinion toward cognitive enhancement. We recruited 3,727 participants from the United States to complete three surveys using Amazon's Mechanical Turk between April and July 2017. Participants read vignettes describing an individual using cognitive enhancement, varying framing metaphors (fuel versus steroid), and context of use (athletes versus students versus employees). The main outcome measure was the difference in respondent-assigned level of acceptability of the use of cognitive enhancement by others and by themselves between the contrasting vignettes. Participants were more likely to support the use of cognitive enhancement by others than by themselves and more when the use of enhancement by others was framed with a fuel metaphor than with a steroid metaphor. Metaphoric framing did not affect participants' attitudes toward their own use. Participants supported the use of enhancement by employees more than by students or athletes. These results are discussed in relation to existing ethical and policy literature.

Growth disturbances associated with untreated benign bone cysts

BACKGROUND

The occurrence of benign bone cysts adjacent to an active physis may be associated with a physeal arrest. That arrest may result from physeal penetration of the cysts itself, secondary pathologic fracture or the result of surgical curettage.

METHODS

The pre-treatment X-rays of patients attending the Bone Tumor Clinic at the Children's Hospital and Medical Center were reviewed. Those patients presenting with a bone cyst were identified and the affected side was compared to the normal side in order to determine growth discrepancies.

RESULTS

Three cases of benign bone cysts are presented that were located adjacent to a growing physis nad produced growth disturbance in the absence of surgical intervention.

CONCLUSIONS

The risk of growth disturbance in itself should not be a contraindication to surgical intervention.

Reproducibility of interictal spike propagation in children with refractory epilepsy

OBJECTIVE

Interictal spikes are a characteristic feature of invasive electroencephalography (EEG) recordings in children with refractory epilepsy. Spikes frequently co-occur across multiple brain regions with discernable latencies, suggesting that spikes can propagate through distributed neural networks. The purpose of this study was to examine the long-term reproducibility of spike propagation patterns over hours to days of interictal recording.

METHODS

Twelve children (mean age 13.1 years) were retrospectively studied. A mean ± standard deviation (SD) of 47.2 ± 40.1 hours of interictal EEG recordings were examined per patient (range 17.5-166.5 hours). Interictal recordings were divided into 30-minute segments. Networks were extracted based on the frequency of spike coactivation between pairs of electrodes. For each 30-minute segment, electrodes were assigned a "Degree Preference (DP)" based on the tendency to appear upstream or downstream within propagation sequences. The consistency of DPs across segments ("DP-Stability") was quantified using the Spearman rank correlation.

RESULTS

Regions exhibited highly stable preferences to appear upstream, intermediate, or downstream in spike propagation sequences. Across networks, the mean ± SD DP-Stability was 0.88 ± 0.07, indicating that propagation patterns observed in 30-minute segments were representative of the patterns observed in the full interictal window. At the group level, regions involved in seizure generation appeared more upstream in spike propagation sequences.

SIGNIFICANCE

Interictal spike propagation is a highly reproducible output of epileptic networks. These findings shed new light on the spatiotemporal dynamics that may constrain the network mechanisms of refractory epilepsy.

Spatiotemporal dynamics of complement C5a production within bacterial extracellular polymeric substance

Opsonization and anaphylatoxin production are early events in the innate response to bacterial pathogens. Opsonization alone is frequently not lethal and production of anaphy-latoxins, especially C5a, allows for recruitment of cellular defenses. Complement biochemistry is extensively studied and computational models have been reported previously. However, a critical feature of complement-mediated attack is its spatial dependence: diffusion of mediators into and away from a bacterium is central to understanding C5a generation. Spatial dependence is especially important in biofilms, where diffusion limitation is crucial to bacterial counterdefense. Here we develop a model of opsonization and C5a production in the presence of a common blood-borne pathogen, Staphylococcus epidermidis. Our results indicate that when complement attacks a single cell, diffusion into the extracellular polymeric substance (EPS) is complete within 10 ms and that production of C5a peaks over the next 15 min. When longer diffusion lengths (as in an EPS-rich biofilm) are incorporated, diffusion limitation appears such that the intensity and duration of C5a production is increased. However, the amount of C5a produced under several likely clinical scenarios where single cells or sparse biofilms are present is below the kD of the C5a receptor suggesting that complement activation by a single bacterium may be difficult to detect when diffusion is taken into account.

Passive and active markers of cortical excitability in epilepsy

Electroencephalography (EEG) has been the primary diagnostic tool in clinical epilepsy for nearly a century. Its review is performed using qualitative clinical methods that have changed little over time. However, the intersection of higher resolution digital EEG and analytical tools developed in the past decade invites a re-exploration of relevant methodology. In addition to the established spatial and temporal markers of spikes and high-frequency oscillations, novel markers involving advanced postprocessing and active probing of the interictal EEG are gaining ground. This review provides an overview of the EEG-based passive and active markers of cortical excitability in epilepsy and of the techniques developed to facilitate their identification. Several different emerging tools are discussed in the context of specific EEG applications and the barriers we must overcome to translate these tools into clinical practice.

Using Generalized Polyspike Train to Predict Drug-Resistant Idiopathic Generalized Epilepsy

INTRODUCTION

The authors tested the hypothesis that the EEG feature generalized polyspike train (GPT) is associated with drug-resistant idiopathic generalized epilepsy (IGE).

METHODS

The authors conducted a single-center case-control study of patients with IGE who had outpatient EEGs performed between 2016 and 2020. The authors classified patients as drug-resistant or drug-responsive based on clinical review and in a masked manner reviewed EEG data for the presence and timing of GPT (a burst of generalized rhythmic spikes lasting less than 1 second) and other EEG features. A relationship between GPT and drug resistance was tested before and after controlling for EEG duration. The EEG duration needed to observe GPT was also calculated.

RESULTS

One hundred three patients were included (70% drug-responsive and 30% drug-resistant patients). Generalized polyspike train was more prevalent in drug-resistant IGE (odds ratio, 3.8; 95% confidence interval, 1.3-11.4; P = 0.02). This finding persisted when controlling for EEG duration both with stratification and with survival analysis. A median of 6.5 hours (interquartile range, 0.5-12.7 hours) of EEG recording was required to capture the first occurrence of GPT.

CONCLUSIONS

The findings support the hypothesis that GPT is associated with drug-resistant IGE. Prolonged EEG recording is required to identify this feature. Thus, >24-hour EEG recording early in the evaluation of patients with IGE may facilitate prognostication.

Diffusion tensor imaging reveals microstructural differences between subtypes of trigeminal neuralgia

OBJECTIVE

Trigeminal neuralgia (TN) is an uncommon idiopathic facial pain syndrome. To assist in diagnosis, treatment, and research, TN is often classified as type 1 (TN1) when pain is primarily paroxysmal and episodic or type 2 (TN2) when pain is primarily constant in character. Recently, diffusion tensor imaging (DTI) has revealed microstructural changes in the symptomatic trigeminal root and root entry zone of patients with unilateral TN. In this study, the authors explored the differences in DTI parameters between subcategories of TN, specifically TN1 and TN2, in the pontine segment of the trigeminal tract.

METHODS

The authors enrolled 8 patients with unilateral TN1, 7 patients with unilateral TN2, and 23 asymptomatic controls. Patients underwent DTI with parameter measurements in a region of interest within the pontine segment of the trigeminal tract. DTI parameters were compared between groups.

RESULTS

In the pontine segment, the radial diffusivity (p = 0.0049) and apparent diffusion coefficient (p = 0.023) values in TN1 patients were increased compared to the values in TN2 patients and controls. The DTI measures in TN2 were not statistically significant from those in controls. When comparing the symptomatic to asymptomatic sides in TN1 patients, radial diffusivity was increased (p = 0.025) and fractional anisotropy was decreased (p = 0.044) in the symptomatic sides. The apparent diffusion coefficient was increased, with a trend toward statistical significance (p = 0.066).

CONCLUSIONS

Noninvasive DTI analysis of patients with TN may lead to improved diagnosis of TN subtypes (e.g., TN1 and TN2) and improve patient selection for surgical intervention. DTI measurements may also provide insights into prognosis after intervention, as TN1 patients are known to have better surgical outcomes than TN2 patients.

Dark field photoelectron emission microscopy of micron scale few layer graphene

We demonstrate dark field imaging in photoelectron emission microscopy (PEEM) of heterogeneous few layer graphene (FLG) furnace grown on SiC(000-1). Energy-filtered, threshold PEEM is used to locate distinct zones of FLG graphene. In each region, selected by a field aperture, the k-space information is imaged using appropriate transfer optics. By selecting the photoelectron intensity at a given wave vector and using the inverse transfer optics, dark field PEEM gives a spatial distribution of the angular photoelectron emission. In the results presented here, the wave vector coordinates of the Dirac cones characteristic of commensurate rotations of FLG on SiC(000-1) are selected providing a map of the commensurate rotations across the surface. This special type of contrast is therefore a method to map the spatial distribution of the local band structure and offers a new laboratory tool for the characterisation of technically relevant, microscopically structured matter.

A pharmacokinetic model of antiseizure medication load to guide care in the epilepsy monitoring unit

OBJECTIVE

Evaluating patients with drug-resistant epilepsy often requires inducing seizures by tapering antiseizure medications (ASMs) in the epilepsy monitoring unit (EMU). The relationship between ASM taper strategy, seizure timing, and severity remains unclear. In this study, we developed and validated a pharmacokinetic model of total ASM load and tested its association with seizure occurrence and severity in the EMU.

METHODS

We studied 80 patients who underwent intracranial electroencephalographic recording for epilepsy surgery planning. We developed a first order pharmacokinetic model of the ASMs administered in the EMU to generate a continuous metric of overall ASM load. We then related modeled ASM load to seizure likelihood and severity. We determined the association between the rate of ASM load reduction, the length of hospital stay, and the probability of having a severe seizure. Finally, we used modeled ASM load to predict oncoming seizures.

RESULTS

Seizures occurred in the bottom 50th percentile of sampled ASM loads across the cohort (p < .0001, Wilcoxon signed-rank test), and seizures requiring rescue therapy occurred at lower ASM loads than seizures that did not require rescue therapy (logistic regression mixed effects model, odds ratio = .27, p = .01). Greater ASM decrease early in the EMU was not associated with an increased likelihood of having a severe seizure, nor with a shorter length of stay.

SIGNIFICANCE

A pharmacokinetic model can accurately estimate ASM levels for patients in the EMU. Lower modeled ASM levels are associated with increased seizure likelihood and seizure severity. We show that ASM load, rather than ASM taper speed, is associated with severe seizures. ASM modeling has the potential to help optimize taper strategy to minimize severe seizures while maximizing diagnostic yield.