An Evaluation of Fit Indices Used in Model Selection of Dichotomous Mixture IRT Models

A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's information criterion (DIC), sample size adjusted BIC (SABIC), relative entropy, the integrated classification likelihood criterion (ICL-BIC), the adjusted Lo-Mendell-Rubin (LMR), and Vuong-Lo-Mendell-Rubin (VLMR). The accuracy of the fit indices was assessed for correct detection of the number of latent classes for different simulation conditions including sample size (2,500 and 5,000), test length (15, 30, and 45), mixture proportions (equal and unequal), number of latent classes (2, 3, and 4), and latent class separation (no-separation and small separation). Simulation study results indicated that as the number of examinees or number of items increased, correct identification rates also increased for most of the indices. Correct identification rates by the different fit indices, however, decreased as the number of estimated latent classes or parameters (i.e., model complexity) increased. Results were good for BIC, CAIC, DIC, SABIC, ICL-BIC, LMR, and VLMR, and the relative entropy index tended to select correct models most of the time. Consistent with previous studies, AIC and AICc showed poor performance. Most of these indices had limited utility for three-class and four-class mixture 3PL model conditions.

Exploring examinees' responses to constructed response items with a supervised topic model

Textual data are increasingly common in test data as many assessments include constructed response (CR) items as indicators of participants' understanding. The development of techniques based on natural language processing has made it possible for researchers to rapidly analyse large sets of textual data. One family of statistical techniques for this purpose are probabilistic topic models. Topic modelling is a technique for detecting the latent topic structure in a collection of documents and has been widely used to analyse texts in a variety of areas. The detected topics can reveal primary themes in the documents, and the relative use of topics can be useful in investigating the variability of the documents. Supervised latent Dirichlet allocation (SLDA) is a popular topic model in that family that jointly models textual data and paired responses such as could occur with participants' textual answers to CR items and their rubric-based scores. SLDA has an assumption of a homogeneous relationship between textual data and paired responses across all documents. This approach, while useful for some purposes, may not be satisfied for situations in which a population has subgroups that have different relationships. In this study, we introduce a new supervised topic model that incorporates finite-mixture modelling into the SLDA. This new model can detect latent groups of participants that have different relationships between their textual responses and associated scores. The model is illustrated with an example from an analysis of a set of textual responses and paired scores from a middle grades assessment of science inquiry knowledge. A simulation study is presented to investigate the performance of the proposed model under practical testing conditions.

Sequential Bayesian Ability Estimation Applied to Mixed-Format Item Tests

Large-scale tests often contain mixed-format items, such as when multiple-choice (MC) items and constructed-response (CR) items are both contained in the same test. Although previous research has analyzed both types of items simultaneously, this may not always provide the best estimate of ability. In this paper, a two-step sequential Bayesian (SB) analytic method under the concept of empirical Bayes is explored for mixed item response models. This method integrates ability estimates from different item formats. Unlike the empirical Bayes method, the SB method estimates examinees' posterior ability parameters with individual-level sample-dependent prior distributions estimated from the MC items. Simulations were used to evaluate the accuracy of recovery of ability and item parameters over four factors: the type of the ability distribution, sample size, test length (number of items for each item type), and person/item parameter estimation method. The SB method was compared with a traditional concurrent Bayesian (CB) calibration method, EAPsum, that uses scaled scores for summed scores to estimate parameters from the MC and CR items simultaneously in one estimation step. From the simulation results, the SB method showed more accurate and reliable ability estimation than the CB method, especially when the sample size was small (150 and 500). Both methods presented similar recovery results for MC item parameters, but the CB method yielded a bit better recovery of the CR item parameters. The empirical example suggested that posterior ability estimated by the proposed SB method had higher reliability than the CB method.

The Impact of Sample Size and Various Other Factors on Estimation of Dichotomous Mixture IRT Models

The purpose of this study was to examine the effects of different data conditions on item parameter recovery and classification accuracy of three dichotomous mixture item response theory (IRT) models: the Mix1PL, Mix2PL, and Mix3PL. Manipulated factors in the simulation included the sample size (11 different sample sizes from 100 to 5000), test length (10, 30, and 50), number of classes (2 and 3), the degree of latent class separation (normal/no separation, small, medium, and large), and class sizes (equal vs. nonequal). Effects were assessed using root mean square error (RMSE) and classification accuracy percentage computed between true parameters and estimated parameters. The results of this simulation study showed that more precise estimates of item parameters were obtained with larger sample sizes and longer test lengths. Recovery of item parameters decreased as the number of classes increased with the decrease in sample size. Recovery of classification accuracy for the conditions with two-class solutions was also better than that of three-class solutions. Results of both item parameter estimates and classification accuracy differed by model type. More complex models and models with larger class separations produced less accurate results. The effect of the mixture proportions also differentially affected RMSE and classification accuracy results. Groups of equal size produced more precise item parameter estimates, but the reverse was the case for classification accuracy results. Results suggested that dichotomous mixture IRT models required more than 2,000 examinees to be able to obtain stable results as even shorter tests required such large sample sizes for more precise estimates. This number increased as the number of latent classes, the degree of separation, and model complexity increased.

Corrigendum: Integrating a Statistical Topic Model and a Diagnostic Classification Model for Analyzing Items in a Mixed Format Assessment

[This corrects the article DOI: 10.3389/fpsyg.2020.579199.].

Integrating a Statistical Topic Model and a Diagnostic Classification Model for Analyzing Items in a Mixed Format Assessment

Selected response items and constructed response (CR) items are often found in the same test. Conventional psychometric models for these two types of items typically focus on using the scores for correctness of the responses. Recent research suggests, however, that more information may be available from the CR items than just scores for correctness. In this study, we describe an approach in which a statistical topic model along with a diagnostic classification model (DCM) was applied to a mixed item format formative test of English and Language Arts. The DCM was used to estimate students’ mastery status of reading skills. These mastery statuses were then included in a topic model as covariates to predict students’ use of each of the latent topics in their written answers to a CR item. This approach enabled investigation of the effects of mastery status of reading skills on writing patterns. Results indicated that one of the skills, Integration of Knowledge and Ideas, helped detect and explain students’ writing patterns with respect to students’ use of individual topics.

Sample Size Requirements for Applying Diagnostic Classification Models

Results of a comprehensive simulation study are reported investigating the effects of sample size, test length, number of attributes and base rate of mastery on item parameter recovery and classification accuracy of four DCMs (i.e., C-RUM, DINA, DINO, and LCDMREDUCED). Effects were evaluated using bias and RMSE computed between true (i.e., generating) parameters and estimated parameters. Effects of simulated factors on attribute assignment were also evaluated using the percentage of classification accuracy. More precise estimates of item parameters were obtained with larger sample size and longer test length. Recovery of item parameters decreased as the number of attributes increased from three to five but base rate of mastery had a varying effect on the item recovery. Item parameter and classification accuracy were higher for DINA and DINO models.

Solar irradiance and ENSO affect food security in Lake Tanganyika, a major African inland fishery

Food security in a warming world is a grave concern for rapidly growing impoverished populations. Low-latitude inland fisheries provide protein for millions of rural poor, yet the impacts of high-frequency climate oscillations on these aquatic ecosystems are unknown. Here, we present a sub-annual-to-annual resolution paleolimnological reconstruction of upwelling, productivity, and algal composition at Lake Tanganyika, one of Africa's largest landlocked fisheries. The data reveal increases in diatom production at centennial-scale solar irradiance maxima, and interannual variability in upwelling linked to La Niña. Our study shows that interactions between global climatic controls and El Niño-Southern Oscillation teleconnections exert profound influences on the foundation of Lake Tanganyika's food web. Adapting long-term management practices to account for high-frequency changes in algal production will help safeguard inland fish resources.

The Impact of Markov Chain Convergence on Estimation of Mixture IRT Model Parameters

A nonconverged Markov chain can potentially lead to invalid inferences about model parameters. The purpose of this study was to assess the effect of a nonconverged Markov chain on the estimation of parameters for mixture item response theory models using a Markov chain Monte Carlo algorithm. A simulation study was conducted to investigate the accuracy of model parameters estimated with different degree of convergence. Results indicated the accuracy of the estimated model parameters for the mixture item response theory models decreased as the number of iterations of the Markov chain decreased. In particular, increasing the number of burn-in iterations resulted in more accurate estimation of mixture IRT model parameters. In addition, the different methods for monitoring convergence of a Markov chain resulted in different degrees of convergence despite almost identical accuracy of estimation.

Comparison of Scale Identification Methods in Mixture IRT Models

The effects of three scale identification constraints in mixture IRT models were studied. A simulation study found no constraint effect on the mixture Rasch and mixture 2PL models, but the item anchoring constraint was the only one that worked well on selecting correct model with the mixture 3PL model.

The Impact of Test and Sample Characteristics on Model Selection and Classification Accuracy in the Multilevel Mixture IRT Model

The standard item response theory (IRT) model assumption of a single homogenous population may be violated in real data. Mixture extensions of IRT models have been proposed to account for latent heterogeneous populations, but these models are not designed to handle multilevel data structures. Ignoring the multilevel structure is problematic as it results in lower-level units aggregated with higher-level units and yields less accurate results, because of dependencies in the data. Multilevel data structures cause such dependencies between levels but can be modeled in a straightforward way in multilevel mixture IRT models. An important step in the use of multilevel mixture IRT models is the fit of the model to the data. This fit is often determined based on relative fit indices. Previous research on mixture IRT models has shown that performances of these indices and classification accuracy of these models can be affected by several factors including percentage of class-variant items, number of items, magnitude and size of clusters, and mixing proportions of latent classes. As yet, no studies appear to have been reported examining these issues for multilevel extensions of mixture IRT models. The current study aims to investigate the effects of several features of the data on the accuracy of model selection and parameter recovery. Results are reported on a simulation study designed to examine the following features of the data: percentages of class-variant items (30, 60, and 90%), numbers of latent classes in the data (with from 1 to 3 latent classes at level 1 and 1 and 2 latent classes at level 2), numbers of items (10, 30, and 50), numbers of clusters (50 and 100), cluster size (10 and 50), and mixing proportions [equal (0.5 and 0.5) vs. non-equal (0.25 and 0.75)]. Simulation results indicated that multilevel mixture IRT models resulted in less accurate estimates when the number of clusters and the cluster size were small. In addition, mean Root mean square error (RMSE) values increased as the percentage of class-variant items increased and parameters were recovered more accurately under the 30% class-variant item conditions. Mixing proportion type (i.e., equal vs. unequal latent class sizes) and numbers of items (10, 30, and 50), however, did not show any clear pattern. Sample size dependent fit indices BIC, CAIC, and SABIC performed poorly for the smaller level-1 sample size. For the remaining conditions, the SABIC index performed better than other fit indices.

Reliability for Tests With Items Having Different Numbers of Ordered Categories

This study describes a structural equation modeling (SEM) approach to reliability for tests with items having different numbers of ordered categories. A simulation study is provided to compare the performance of this reliability coefficient, coefficient alpha and population reliability for tests having items with different numbers of ordered categories, a one-factor and a bifactor structures, and different skewness distributions of test scores. Results indicated that the proposed reliability coefficient was close to the population reliability in most conditions. An empirical example was used to illustrate the performance of the different coefficients for a test of items with two or three ordered categories.

The Impact of Equating on Detection of Treatment Effects

Equating makes it possible to compare performances on different forms of a test. Three different equating methods (baseline selection, subgroup, and subscore equating) using common-item item response theory equating were examined for their impact on detection of treatment effects in multilevel models.

Model Selection for Multilevel Mixture Rasch Models

Mixture item response theory (MixIRT) models can sometimes be used to model the heterogeneity among the individuals from different subpopulations, but these models do not account for the multilevel structure that is common in educational and psychological data. Multilevel extensions of the MixIRT models have been proposed to address this shortcoming. Successful applications of multilevel MixIRT models depend in part on detection of the best fitting model. In this study, performance of information indices, Akaike information criterion (AIC), Bayesian information criterion (BIC), consistent Akaike information criterion (CAIC), and sample-size adjusted Bayesian information criterion (SABIC), were compared for use in model selection with a two-level mixture Rasch model in the context of a real data example and a simulation study. Level 1 consisted of students and Level 2 consisted of schools. The performances of the model selection criteria under different sample sizes were investigated in a simulation study. Total sample size (number of students) and Level 2 sample size (number of schools) were studied for calculation of information criterion indices to examine the performance of these fit indices. Simulation study results indicated that CAIC and BIC performed better than the other indices at detection of the true (i.e., generating) model. Furthermore, information indices based on total sample size yielded more accurate detections than indices at Level 2.

Use of Information Criteria in the Study of Group Differences in Trace Lines

A brief review of various information criteria is presented for the detection of differential item functioning (DIF) under item response theory (IRT). An illustration of using information criteria for model selection as well as results with simulated data are presented and contrasted with the IRT likelihood ratio (LR) DIF detection method. Use of information criteria for general IRT model selection is discussed.

Priors in Bayesian Estimation under the Rasch Model

A review of various priors used in Bayesian estimation under the Rasch model is presented together with clear mathematical definitions of the hierarchical prior distributions. A Bayesian estimation method, Gibbs sampling, was compared with conditional, marginal, and joint maximum likelihood estimation methods using the Knox Cube Test data under the Rasch model. The shrinkage effect of the priors on item and ability parameter estimates was also investigated using the Knox Cube Test data. In addition, item response data for a mathematics test with 14 items by 765 examinees were analyzed with the joint maximum likelihood estimation method and Gibbs sampling under the Rasch model. Both methods yielded nearly identical item parameter estimates. The shrinkage effect was observed in the ability estimates from Gibbs sampling. The computer program OpenBUGS that implemented the rejection sampling method of Gibbs sampling was the main program employed in the study.

Plasma Concentrations of Long Chain N-3 Fatty Acids in Early and Mid-Pregnancy and Risk of Early Preterm Birth

Background

Fish oil supplementation has been shown to delay spontaneous delivery, but the levels and clinical significance remain uncertain. We examined the association between plasma fatty acids quantified in pregnancy and subsequent risk of early preterm birth.

Methods

In a case-control design nested in the Danish National Birth Cohort, we identified 376 early preterm cases (<34 gestational weeks, excluding preeclampsia cases) and 348 random controls. Plasma eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA% of total fatty acids), were measured twice in pregnancy, at gestation weeks 9 and 25 (medians). Odds ratios and 95% confidence intervals (CI's) for associations between EPA+DHA and early preterm risk were estimated by logistic regression, adjusted for the woman's age, height, pre-pregnancy BMI, parity, smoking, and socioeconomic factors. Hypotheses and analytical plan were defined and archived a priori.

Findings

Analysis using restricted cubic splines of the mean of 1st and 2nd sample measurements showed a strong and significant non-linear association (p < 0.0001) in which the risk of early preterm birth steeply increased when EPA+DHA concentrations were lower than 2% and flattened out at higher levels. Women in the lowest quintile (EPA+DHA < 1.6%) had 10.27 times (95% confidence interval 6.80–15.79, p < 0.0001) increased risk, and women in the second lowest quintile had 2.86 (95% CI 1.79–4.59, p < 0.0001) times increased risk, when compared to women in the three aggregated highest quintiles (EPA+DHA ≥ 1.8%).

Interpretation

Low plasma concentration of EPA and DHA during pregnancy is a strong risk factor for subsequent early preterm birth in Danish women.

Abnormal Blink Reflex Studies in a Patient With Supraorbital Neuralgia

A 44-year-old female with gabapentin-responsive supraorbital neuralgia is presented. She had pre- and post-treatment nociceptive-specific blink reflexes carried out which tracked the good clinical outcome from treatment. The results of the electrophysiological testing imply some central component to the pathophysiology of supra-orbital neuralgia.

Paroxysmal Hemicrania in a Family

Paroxysmal hemicrania (PH) is a trigeminal autonomic cephalgia, characterised by unilateral attacks responsive to indomethacin. There are no published reports of a family history in PH. We report a mother and daughter both with PH. The daughter and her sister also had migraine.

Short-Lasting Unilateral Neuralgiform Headache Attacks with Conjunctival Injection and Tearing

SUNCT (Short-lasting Unilateral Neuralgiform headache attacks with Conjunctival injection and Tearing) and SUNA (Short-lasting Unilateral Neuralgiform headache attacks with cranial Autonomic symptoms) are rare primary headache syndromes, classified as Trigeminal Autonomic Cephalalgias (TACs). Hypothalamic involvement in the TACs has been suggested by functional imaging data and clinically with deep brain stimulation.

Fifty-two patients (43 SUNCT, 9 SUNA) were studied to determine the clinical phenotype of these conditions and response to medications. A functional imaging study explored activation of the posterior hypothalamus in attacks of SUNCT/SUNA.

The clinical study characterised SUNCT and SUNA in terms of epidemiology, phenotype and clinical characteristics.

Indomethacin is ineffective on single-blind testing. Intravenous lidocaine was effective in all cases. Open-label trails showed the effectiveness of lamotrigine, topiramate and gabapentin.

On functional imaging there was hypothalamic activation bilaterally in 5/9 SUNCT patients, and contralaterally in two patients. Two SUNCT patients had ipsilateral negative activation. In SUNA the activation was bilaterally negative. There was no hypothalamic activation in a patient with SUNCT secondary to a brainstem lesion.

The data suggests that there should be revised classification for SUNCT and SUNA, with an increased range of attack duration and frequency, cutaneous triggering of attacks, and a lack of refractory period. The concept of ‘attack load’ is introduced. The lack of response to indomethacin and the response to intravenous lidocaine, are useful in diagnostic and therapeutic terms, respectively. Preventive treatments include lamotrigine, gabapentin and topiramate. The role of hypothalamic involvement in SUNCT and SUNA as TACs is considered.

SUNCT Syndrome Responsive to Intravenous Lidocaine

Short-lasting unilateral neuralgiform headache with conjunctival injection and tearing (SUNCT) is a primary headache syndrome that has been reported to be resistant to treatment with intravenous lidocaine. We report four cases of SUNCT in whom intravenous lidocaine (1.3-3.3 mg kg−1 h−1) completely suppressed the headaches for the duration of the infusion. The headache returned after cessation of treatment. Two patients went on to have their symptoms controlled on topiramate (50-300 mg daily). One patient had typical migrainous aura in association with some of the attacks of pain but never migrainous headaches. These cases suggest that treatment with lidocaine can be considered when acute intervention is required to suppress a severe exacerbation of SUNCT, and further broaden the therapeutic and clinical background of this syndrome.

The Impact of Non-Normality on Extraction of Spurious Latent Classes in Mixture IRT Models

Unidimensional, item response theory (IRT) models assume a single homogeneous population. Mixture IRT (MixIRT) models can be useful when subpopulations are suspected. The usual MixIRT model is typically estimated assuming a normally distributed latent ability. Research on normal finite mixture models suggests that latent classes potentially can be extracted, even in the absence of population heterogeneity, if the distribution of the data is non-normal. In this study, the authors examined the sensitivity of MixIRT models to latent non-normality. Single-class IRT data sets were generated using different ability distributions and then analyzed with MixIRT models to determine the impact of these distributions on the extraction of latent classes. Results suggest that estimation of mixed Rasch models resulted in spurious latent class problems in the data when distributions were bimodal and uniform. Mixture two-parameter logistic (2PL) and mixture three-parameter logistic (3PL) IRT models were found to be more robust to latent non-normality.

Detecting Test Tampering Using Item Response Theory

Test tampering, especially on tests for educational accountability, is an unfortunate reality, necessitating that the state (or its testing vendor) perform data forensic analyses, such as erasure analyses, to look for signs of possible malfeasance. Few statistical approaches exist for detecting fraudulent erasures, and those that do largely do not lend themselves to making probabilistic statements about the likelihood of the observations. In this article, a new erasure detection index, EDI, is developed, which uses item response theory to compare the number of observed wrong-to-right erasures to the number expected due to chance, conditional on the examinee's ability-level and number of erased items. A simulation study is presented to evaluate the Type I error rate and power of EDI under various types of fraudulent and benign erasures. Results show that EDI with a correction for continuity yields Type I error rates that are less than or equal to nominal levels for every condition studied, and has high power to detect even small amounts of tampering among the students for whom tampering is most likely.

Elevated fetal steroidogenic activity in autism

Autism affects males more than females, giving rise to the idea that the influence of steroid hormones on early fetal brain development may be one important early biological risk factor. Utilizing the Danish Historic Birth Cohort and Danish Psychiatric Central Register, we identified all amniotic fluid samples of males born between 1993 and 1999 who later received ICD-10 (International Classification of Diseases, 10th Revision) diagnoses of autism, Asperger syndrome or PDD-NOS (pervasive developmental disorder not otherwise specified) (n=128) compared with matched typically developing controls. Concentration levels of Δ4 sex steroids (progesterone, 17α-hydroxy-progesterone, androstenedione and testosterone) and cortisol were measured with liquid chromatography tandem mass spectrometry. All hormones were positively associated with each other and principal component analysis confirmed that one generalized latent steroidogenic factor was driving much of the variation in the data. The autism group showed elevations across all hormones on this latent generalized steroidogenic factor (Cohen's d=0.37, P=0.0009) and this elevation was uniform across ICD-10 diagnostic label. These results provide the first direct evidence of elevated fetal steroidogenic activity in autism. Such elevations may be important as epigenetic fetal programming mechanisms and may interact with other important pathophysiological factors in autism.

Detecting intervention effects using a multilevel latent transition analysis with a mixture IRT model

A multilevel latent transition analysis (LTA) with a mixture IRT measurement model (MixIRTM) is described for investigating the effectiveness of an intervention. The addition of a MixIRTM to the multilevel LTA permits consideration of both potential heterogeneity in students' response to instructional intervention as well as a methodology for assessing stage sequential change over time at both student and teacher levels. Results from an LTA-MixIRTM and multilevel LTA-MixIRTM were compared in the context of an educational intervention study. Both models were able to describe homogeneities in problem solving and transition patterns. However, ignoring a multilevel structure in LTA-MixIRTM led to different results in group membership assignment in empirical results. Results for the multilevel LTA-MixIRTM indicated that there were distinct individual differences in the different transition patterns. The students receiving the intervention treatment outscored their business as usual (i.e., control group) counterparts on the curriculum-based Fractions Computation test. In addition, 27.4 % of the students in the sample moved from the low ability student-level latent class to the high ability student-level latent class. Students were characterized differently depending on the teacher-level latent class.

Paroxysmal hemicrania responding to topiramate

Chronic paroxysmal hemicrania (CPH) is a rare primary headache syndrome, which is classified along with cluster headache and short-lasting unilateral neuralgiform headache attacks with conjunctival injection and tearing (SUNCT) as a trigeminal autonomic cephalalgia. CPH is exquisitely responsive to indomethacin, so much so that the response is one of the current diagnostic criteria. The case of a patient with CPH, who had marked epigastric symptoms with indomethacin treatment and responded well to topiramate 150 mg daily, is reported. Cessation of topiramate caused return of episodes, and the response has persisted for 2 years. Topiramate may be a treatment option in CPH.

Arousability in schizophrenia: relationship to emotional and physiological reactivity and symptom severity

OBJECTIVE

Socioenvironmental stressors have been linked with increased symptom severity and relapse in those with schizophrenia. However, little is known about how individual differences in stress reactivity may contribute to these outcomes.

METHOD

This study examined the association between the temperament characteristic of arousability and changes in negative affect and cardiovascular activity during a challenge task in 58 in-patients with diagnosis of schizophrenia and 21 controls.

RESULTS

In the patient group, levels of arousability were significantly associated with increases in negative affect in response to the task and greater severity of affective symptoms. Levels of arousability were associated with decreased heart rate during the challenge task in our patient group.

CONCLUSION

These findings suggest that greater attention be given to individual differences, such as temperament and personality characteristics, and their role in the experience of stressors, including emotional and physiological response, as well as symptom development.

Unilateral photophobia or phonophobia in migraine compared with trigeminal autonomic cephalalgias

Our objective was to compare the presence of self-reported unilateral photophobia or phonophobia, or both, during headache attacks comparing patients with trigeminal autonomic cephalalgias (TACs)--including cluster headache, short-lasting unilateral neuralgiform headache attacks with conjunctival injection and tearing (SUNCT) and paroxysmal hemicrania--or hemicrania continua, and other headache types. We conducted a prospective study in patients attending a referral out-patient clinic over 5 months and those admitted for an intramuscular indomethacin test. Two hundred and six patients were included. In episodic migraine patients, two of 54 (4%) reported unilateral photophobia or phonophobia, or both. In chronic migraine patients, six of 48 (13%) complained of unilateral photophobia or phonophobia, or both, whereas none of the 24 patients with medication-overuse headache reported these unilateral symptoms, although these patients all had clinical symptoms suggesting the diagnosis of migraine. Only three of 22 patients (14%) suffering from new daily persistent headache (NDPH) experienced unilateral photophobia or phonophobia. In chronic cluster headache 10 of 21 patients (48%) had unilateral photophobia or phonophobia, or both, and this symptom appeared in four of five patients (80%) with episodic cluster headache. Unilateral photophobia or phonophobia, or both, were reported by six of 11 patients (55%) with hemicrania continua, five of nine (56%) with SUNCT, and four of six (67%) with chronic paroxysmal hemicrania. Unilateral phonophobia or photophobia, or both, are more frequent in TACs and hemicrania continua than in migraine and NDPH. The presence of these unilateral symptoms may be clinically useful in the differential diagnosis of primary headaches.

Neurotrophin-mediated neuroprotection of hippocampal neurons following traumatic brain injury is not associated with acute recovery of hippocampal function

Traumatic brain injury (TBI) causes selective hippocampal cell death which is believed to be associated with the cognitive impairment observed in both clinical and experimental settings. The endogenous neurotrophin-4/5 (NT-4/5), a TrkB ligand, has been shown to be neuroprotective for vulnerable CA3 pyramidal neurons after experimental brain injury. In this study, infusion of recombinant NT-4/5 increased survival of CA2/3 pyramidal neurons to 71% after lateral fluid percussion brain injury in rats, compared with 55% in vehicle-treated controls. The functional outcome of this NT-4/5-mediated neuroprotection was examined using three hippocampal-dependent behavioral tests. Injury-induced impairment was evident in all three tests, but interestingly, there was no treatment-related improvement in any of these measures. Similarly, injury-induced decreased excitability in the Schaffer collaterals was not affected by NT-4/5 treatment. We propose that a deeper understanding of the factors that link neuronal survival to recovery of function will be important for future studies of potentially therapeutic agents.

Paroxysmal hemicrania responding to topiramate

Chronic paroxysmal hemicrania (CPH) is a rare primary headache syndrome, which is classified along with cluster headache and short-lasting unilateral neuralgiform headache attacks with conjunctival injection and tearing (SUNCT) as a trigeminal autonomic cephalalgia. CPH is exquisitely responsive to indomethacin so much so that the response is one of the current diagnostic criteria. The case of a patient with CPH, who had marked epigastric symptoms with indomethacin treatment and responded well to topiramate 150 mg daily, is reported. Cessation of topiramate caused return of episodes, and the response has persisted for 2 years. Topiramate may be a treatment option in CPH.

Mechanisms underlying the inability to induce area CA1 LTP in the mouse after traumatic brain injury

Traumatic brain injury (TBI) is a significant health issue that often causes enduring cognitive deficits, in particular memory dysfunction. The hippocampus, a structure crucial in learning and memory, is frequently damaged during TBI. Since long-term potentiation (LTP) is the leading cellular model underlying learning and memory, this study was undertaken to examine how injury affects area CA1 LTP in mice using lateral fluid percussion injury (FPI). Brain slices derived from FPI animals demonstrated an inability to induce LTP in area CA1 7 days postinjury. However, area CA1 long-term depression could be induced in neurons 7 days postinjury, demonstrating that some forms of synaptic plasticity can still be elicited. Using a multi-disciplined approach, potential mechanisms underlying the inability to induce and maintain area CA1 LTP were investigated. This study demonstrates that injury leads to significantly smaller N-methyl-D-aspartate potentials and glutamate-induced excitatory currents, increased dendritic spine size, and decreased expression of alpha-calcium calmodulin kinase II. These findings may underlie the injury-induced lack of LTP and thus, contribute to cognitive impairments often associated with TBI. Furthermore, these results provide attractive sites for potential therapeutic intervention directed toward alleviating the devastating consequences of human TBI.

Regional hippocampal alteration associated with cognitive deficit following experimental brain injury: a systems, network and cellular evaluation

Cognitive deficits persist in patients who survive traumatic brain injury (TBI). Lateral fluid percussion brain injury in the mouse, a model of human TBI, results in hippocampal-dependent cognitive impairment, similar to retrograde amnesia often associated with TBI. To identify potential substrates of the cognitive impairment, we evaluated regional neuronal loss, regional hippocampal excitability and inhibitory synaptic transmission. Design-based stereology demonstrated an approximate 40% loss of neurons through all subregions of the hippocampus following injury compared with sham. Input/output curves recorded in slices of injured brain demonstrated increased net synaptic efficacy in the dentate gyrus in concert with decreased net synaptic efficacy and excitatory postsynaptic potential-spike relationship in area CA1 compared with sham slices. Pharmacological agents modulating inhibitory transmission partially restored regional injury-induced alterations in net synaptic efficacy. Both evoked and spontaneous miniature inhibitory postsynaptic currents (mIPSCs) recorded in surviving dentate granule neurons were smaller and less frequent in injured brains than in uninjured brains. Conversely, both evoked and spontaneous mIPSCs recorded in surviving area CA1 pyramidal neurons were larger in injured brains than in uninjured brains. Together, these alterations suggest that regional hippocampal function is altered in the injured brain. This study demonstrates for the first time that brain injury selectively disrupts hippocampal function by causing uniform neuronal loss, inhibitory synaptic dysfunction, and regional, but opposing, shifts in circuit excitability. These changes may contribute to the cognitive impairments that result from brain injury.

Characterization of quaternary ammonium oligomers by paired-ion reversed-phase liquid chromatography-mass spectrometry

The separation of novel permanently charged oligomers was studied using paired-ion reversed-phase liquid chromatography. The polyionene studied is less than 5 kDa in size, but contains three oligomer series with different end-group chemistries. The complexity of this polyionene makes development of a single-dimension separation quite challenging. Separation under critical conditions was employed to fractionate the end-group conformations and then the chain length of the oligomers in each series was confirmed by LC-MS. The oligomers were then used to optimize a single-dimension HPLC separation. Precise modulation of the hydrophobicity of the ion-pair reagent and the stationary-phase chemistry yielded very high resolution one-dimensional separations.

Indirect enzyme-linked immunosorbent assay for the detection of antibody against Rift Valley fever virus in domestic and wild ruminant sera

An indirect enzyme-linked immunosorbent assay (I-ELISA) for the detection of specific IgG immunoglobulins against Rift Valley fever virus (RVFV) was validated in-house. A total of 3055 sera from sheep (n = 1159), goats (n = 636), cattle (n = 203), African buffalo (n = 928), and other wild ruminants (n = 129), including eland, kudu, and black wildebeest, was used. Sera from domestic ruminants were collected in West (n = 10), South (n = 1654) and East Africa (n = 334), and sera from wild ruminants (n = 1064) were collected in South Africa. In addition, 136 sera from eight experimentally RVFV-infected sheep, taken during a period of 28 days post infection (dpi), were used to study the kinetics of RVFV antibody production. Field sera were tested by the serum neutralization (VN) test and experimental sera by VN and haemagglutination-inhibition (HI) test. Based on VN test results, negative sera were regarded as reference controls from RVFV-free, and positive sera were regarded as reference controls from RVFV-infected subpopulations of animals. ELISA data were expressed as the percentage positivity (PP) of an internal high positive control. The two-graph receiver operating characteristics approach was used for the selection and optimization of I-ELISA cut-offs including the misclassification costs term and Youden index (J). In addition, cut-off values were determined as the mean plus two-fold standard deviation of the result observed with the RVFV-free subpopulations. Established optimal cut-offs were different for each of the data sets analyzed, and ranged from 1.65 PP (buffalo) to 9.1 PP (goats). At the cut-off giving the highest estimate of combined measure of diagnostic accuracy (highest J value), the I-ELISA test parameters were determined as follows: (1) Diagnostic sensitivity (%): cattle--84.31, buffalo--94.44, sheep--98.91, goats--99.18. (2) Diagnostic specificity (%): cattle--99.34, buffalo--98.28, sheep--99.16, goats--99.23 and other game ruminants--99.26. In the group of RVFV-experimentally infected sheep, seroconversion In all individuals was detected by VN on 4-6 dpi, by HI on 5-7 dpi, and by I-ELISA on 6-7 dpi. All tests showed the same kinetic pattern of immunological response. Antibody levels were low for a very short period before increasing to high titres, after which it was easily detectable by all tests. Compared to traditional tests, the lower sensitivity of I-ELISA in the detection of the earliest stage of immunological response may be practically insignificant, particularily when this assay is used in population-based, disease-surveillance programmes. The high sensitivity and specificity of I-ELISA established in this study, especially for the statistically more representative subpopulations of animals tested, seem to support this prediction. Test parameters determined in this study should, however, be regarded as in-house diagnostic decision limits, for which further updating is recommended, particularly for specimens from other countries, and preferably by applying a standardized method for sampling of new subpopulations of animals to be targeted by the assay.

Specific proteolysis of the NR2 subunit at multiple sites by calpain

The NMDA subtype of glutamate receptor plays an important role in the molecular mechanisms of learning, memory and excitotoxicity. NMDA receptors are highly permeable to calcium, which can lead to the activation of the calcium-dependent protease, calpain. In the present study, the ability of calpain to modulate NMDA receptor function through direct proteolytic digestion of the individual NMDA receptor subunits was examined. HEK293t cells were cotransfected with the NR1a/2A, NR1a/2B or NR1a/2C receptor combinations. Cellular homogenates of these receptor combinations were prepared and digested by purified calpain I in vitro. All three NR2 subunits could be proteolyzed by calpain I while no actin or NR1a cleavage was observed. Based on immunoblot analysis, calpain cleavage of NR2A, NR2B and NR2C subunits was limited to their C-terminal region. In vitro calpain digestion of fusion protein constructs containing the C-terminal region of NR2A yielded two cleavage sites at amino acids 1279 and 1330. Although it has been suggested that calpain cleavage of the NMDA receptor may act as a negative feedback mechanism, the current findings demonstrated that calpain cleavage did not alter [(125)I]MK801 binding and that receptors truncated to the identified cleavage sites had peak intracellular calcium levels, (45)Ca uptake rates and basal electrophysiological properties similar to wild type.

Affective reactivity of language symptoms, startle responding, and inhibition in schizophrenia

The speech of some schizophrenia patients becomes markedly more disordered when negative affect is aroused. The authors tested associations between affective reactivity of speech and responsiveness and inhibition on an acoustic startle task in a sample of 27 outpatients. Patients whose language was reactive to negative affect showed significantly higher initial startle amplitudes than those whose language was not reactive. However, they also showed greater habituation to repeated startle stimuli over trials, even after differences in initial amplitudes were controlled statistically. These findings suggest that affective reactivity of speech is associated with higher initial startle responsiveness but also with greater habituation and, conversely, that patients who are relatively nonreactive to excitatory affective and sensory stimuli are also less reactive to inhibitory input.

Zinc-induced augmentation of excitatory synaptic currents and glutamate receptor responses in hippocampal CA3 neurons

Zinc is found throughout the CNS at synapses co-localized with glutamate in presynaptic terminals. In particular, dentate granule cells' (DGC) mossy fiber (MF) axons contain especially high concentrations of zinc co-localized with glutamate within vesicles. To study possible physiological roles of zinc, visualized slice-patch techniques were used to voltage-clamp rat CA3 pyramidal neurons, and miniature excitatory postsynaptic currents (mEPSCs) were isolated. Bath-applied zinc (200 microM) enhanced median mEPSC peak amplitudes to 153.0% of controls, without affecting mEPSC kinetics. To characterize this augmentation further, rapid agonist application was performed on perisomatic outside-out patches to coapply zinc with glutamate extremely rapidly for brief (1 ms) durations, thereby emulating release kinetics of these substances at excitatory synapses. When zinc was coapplied with glutamate, zinc augmented peak glutamate currents (mean +/- SE, 116.6 +/- 2.8% and 143.8 +/- 9.8% of controls at 50 and 200 microM zinc, respectively). This zinc-induced potentiation was concentration dependent, and pharmacological isolation of alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor-mediated currents (AMPAR currents) gave results similar to those observed with glutamate application (mean, 115.0 +/- 5.4% and 132.5 +/- 9.1% of controls at 50 and 200 microM zinc, respectively). Inclusion of the AMPAR desensitization blocker cyclothiazide in the control solution, however, abolished zinc-induced augmentation of glutamate-evoked currents, suggesting that zinc may potentiate AMPAR currents by inhibiting AMPAR desensitization. Based on the results of the present study, we hypothesize that zinc is a powerful modulator of both excitatory synaptic transmission and glutamate-evoked currents at physiologically relevant concentrations. This modulatory role played by zinc may be a significant factor in enhancing excitatory neurotransmission and could significantly regulate function at the mossy fiber-CA3 synapse.

Affective reactivity of language symptoms, startle responding, and inhibition in schizophrenia

The speech of some schizophrenia patients becomes markedly more disordered when negative affect is aroused. The authors tested associations between affective reactivity of speech and responsiveness and inhibition on an acoustic startle task in a sample of 27 outpatients. Patients whose language was reactive to negative affect showed significantly higher initial startle amplitudes than those whose language was not reactive. However, they also showed greater habituation to repeated startle stimuli over trials, even after differences in initial amplitudes were controlled statistically. These findings suggest that affective reactivity of speech is associated with higher initial startle responsiveness but also with greater habituation and, conversely, that patients who are relatively nonreactive to excitatory affective and sensory stimuli are also less reactive to inhibitory input.