Cerebrospinal fluid sodium rhythms

Background: Cerebrospinal fluid (CSF) sodium levels have been reported to rise during episodic migraine. Since migraine frequently starts in early morning or late afternoon, we hypothesized that natural sodium chronobiology may predispose susceptible persons when extracellular CSF sodium increases. Since no mammalian brain sodium rhythms are known, we designed a study of healthy humans to test if cation rhythms exist in CSF. Methods: Lumbar CSF was collected every ten minutes at 0.1 mL/min for 24 h from six healthy participants. CSF sodium and potassium concentrations were measured by ion chromatography, total protein by fluorescent spectrometry, and osmolarity by freezing point depression. We analyzed cation and protein distributions over the 24 h period and spectral and permutation tests to identify significant rhythms. We applied the False Discovery Rate method to adjust significance levels for multiple tests and Spearman correlations to compare sodium fluctuations with potassium, protein, and osmolarity. Results: The distribution of sodium varied much more than potassium, and there were statistically significant rhythms at 12 and 1.65 h periods. Curve fitting to the average time course of the mean sodium of all six subjects revealed the lowest sodium levels at 03.20 h and highest at 08.00 h, a second nadir at 09.50 h and a second peak at 18.10 h. Sodium levels were not correlated with potassium or protein concentration, or with osmolarity. Conclusion: These CSF rhythms are the first reports of sodium chronobiology in the human nervous system. The results are consistent with our hypothesis that rising levels of extracellular sodium may contribute to the timing of migraine onset. The physiological importance of sodium in the nervous system suggests that these rhythms may have additional repercussions on ultradian functions

The initial education of high school teachers : a critical review of major issues and trends

This paper draws on major research findings in international literature in order to provide a critical review of a number of key issues and trends in the initial education of high school teachers. Firstly, this paper contextualizes the prevalent discourse surrounding the field of initial teacher education (ITE) and explores the effect that this discourse has on the conceptualization of teachers’ work. Secondly, this paper focuses on the debates regarding the most propitious site for the teacher education enterprise, the programme structure for ITE, the field placement or practicum, the relationship between subject study and pedagogy, and the overall effectiveness of teacher education. The paper concludes by considering the new challenges that the field of initial teacher education must confront and the implications of such challenges for the ITE curriculum.peer-reviewe

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Central Neurochemical Ultradian Variability in Depression

Depression is characterized by blunted behavior and neuroendocrine function that generally improve with antidepressant treatment. This study examined intrinsic variability in brain neurotransmitter function, since it may be a source of blunted behavior and neuroendocrine function in depression and a marker for the illness, and has not previously been analyzed using wavelet decomposition. To measure variability in monoamine metabolites, lumbar cerebrospinal fluid (CSF) was collected in serial samples in depressed patients before and after treatment. We hypothesized that changes in variability would be observed after treatment. Mechanisms that control such variability may be critical to the pathophysiology of depression. Method: Time series data was obtained from serial ten-min sampling over a 24-hr period (N = 144) from thirteen depressed patients, with a repeat collection after 5 weeks of antidepressant (sertraline or bupropion) treatment. Concentrations of tryptophan (TRP), the monoamine metabolites 5-HIAA (metabolite of serotonin) and HVA (metabolite of dopamine), and the HVA:5HIAA ratio were transformed to examine power in slowly (160 min/cycle) to rapidly (20 min/cycle) occurring events. Power, the sum of the squares of the coefficients in each d (detail) wavelet, reflects variability within a limited frequency bandwidth for that wavelet. Pre-treatment to post-treatment comparisons were conducted with repeated measures ANOVA. Results: Antidepressant treatment was associated with increased power in the d2 wavelet from the HVA (p = 0.03) and the HVA:5-HIAA ratio (p = 0.03) series. The d1 and d3 wavelets showed increased power following antidepressant treatment for the ratio series (d1, p = 0.01; d3, p = 0.05). Significant changes in power were not observed for the 5-HIAA data series. Power differences among analytes suggest that the findings are specific to each system. Conclusion: The wavelet transform analysis shows changes in neurochemical signal variability following antidepressant treatment. Patterns or degrees of variability may be as important as, or possibly more important than, the mean levels of monoamine transmitters. Studies of variability observed in healthy individuals and a larger depressed sample will be needed to verify a relationship with mood and treatment response. Neurochemical measures of time-variability may be a pivotal marker in depression

Central neurochemical ultradian variability in depression

Abstract. Depression is characterized by blunted behavior and neuroendocrine function that generally improve with antidepressant treatment. This study examined intrinsic variability in brain neurotransmitter function, since it may be a source of blunted behavior and neuroendocrine function in depression and a marker for the illness, and has not previously been analyzed using wavelet decomposition. To measure variability in monoamine metabolites, lumbar cerebrospinal fluid (CSF) was collected in serial samples in depressed patients before and after treatment. We hypothesized that changes in variability would be observed after treatment. Mechanisms that control such variability may be critical to the pathophysiology of depression. Method: Time series data was obtained from serial ten-min sampling over a 24-hr period (N = 144) from thirteen depressed patients, with a repeat collection after 5 weeks of antidepressant (sertraline or bupropion) treatment. Concentrations of tryptophan (TRP), the monoamine metabolites 5-HIAA (metabolite of serotonin) and HVA (metabolite of dopamine), and the HVA:5HIAA ratio were transformed to examine power in slowly (160 min/cycle) to rapidly (20 min/cycle) occurring events. Power, the sum of the squares of the coefficients in each d (detail) wavelet, reflects variability within a limited frequency bandwidth for that wavelet. Pre-treatment to post-treatment comparisons were conducted with repeated measures ANOVA. Results: Antidepressant treatment was associated with increased power in the d2 wavelet from the HVA (p = 0.03) and the HVA:5-HIAA ratio (p = 0.03) series. The d1 and d3 wavelets showed increased power following antidepressant treatment for the ratio series (d1, p = 0.01; d3, p = 0.05). Significant changes in power were not observed for the 5-HIAA data series. Power differences among analytes suggest that the findings are specific to each system. Conclusion: The wavelet transform analysis shows changes in neurochemical signal variability following antidepressant treatment. Patterns or degrees of variability may be as important as, or possibly more important than, the mean levels of monoamine transmitters. Studies of variability observed in healthy individuals and a larger depressed sample will be needed to verify a relationship with mood and treatment response. Neurochemical measures of time-variability may be a pivotal marker in depression

Evaluation of voice acoustics as predictors of clinical depression scores

Summary: Objective. The aim of the present study was to determine if acoustic measures of voice, characterizing specific spectral and timing properties, predict clinical ratings of depression severity measured in a sample of patients using the Hamilton Depression Rating Scale (HAMD) and Beck Depression Inventory (BDI-II). Study Design. This is a prospective study. Methods. Voice samples and clinical depression scores were collected prospectively from consenting adult patients who were referred to psychiatry from the adult emergency department or primary care clinics. The patients were audiorecorded as they read a standardized passage in a nearly closed-room environment. MeanAbsolute Error (MAE) between actual and predicted depression scores was used as the primary outcome measure. Results. The average MAE between predicted and actual HAMD scores was approximately two scores for both men and women, and the MAE for the BDI-II scores was approximately one score for men and eight scores for women. Timing features were predictive of HAMD scores in female patients while a combination of timing features and spectral features was predictive of scores in male patients.Timing features were predictive of BDI-II scores in male patients. Conclusion. Voice acoustic features extracted from read speech demonstrated variable effectiveness in predicting clinical depression scores in men and women. Voice features were highly predictive of HAMD scores in men and women, and BDI-II scores in men, respectively. The methodology is feasible for diagnostic applications in diverse clinical settings as it can be implemented during a standard clinical interview in a normal closed room and without strict control on the recording environment. Key Words: depression–severity–prediction–voice–acoustics