Citalopram and sertraline exposure compromises embryonic bone development

Selective serotonin reuptake inhibitors (SSRIs) are the most commonly prescribed treatments for depression and, as a class of drugs, are among the most used medications in the world. Concern regarding possible effects of SSRI treatment on fetal development has arisen recently as studies have suggested a link between maternal SSRI use and an increase in birth defects such as persistent pulmonary hypertension, seizures and craniosynostosis. Furthermore, SSRI exposure in adults is associated with decreased bone mineral density and increased fracture risk, and serotonin receptors are expressed in human osteoblasts and osteoclasts. To determine possible effects of SSRI exposure on developing bone, we treated both zebrafish, during embryonic development, and human mesenchymal stem cells (MSCs), during differentiation into osteoblasts, with the two most prescribed SSRIs, citalopram and sertraline. SSRI treatment in zebrafish decreased bone mineralization, visualized by alizarin red staining and decreased the expression of mature osteoblast-specific markers during embryogenesis. Furthermore, we showed that this inhibition was not associated with increased apoptosis. In differentiating human MSCs, we observed a decrease in osteoblast activity that was associated with a decrease in expression of the osteoblast-specific genes Runx2, Sparc and Spp1, measured with quantitative real-time PCR (qRT-PCR). Similar to the developing zebrafish, no increase in expression of the apoptotic marker Caspase 3 was observed. Therefore, we propose that SSRIs inhibit bone development by affecting osteoblast maturation during embryonic development and MSC differentiation. These results highlight the need to further investigate the risks of SSRI use during pregnancy in exposing unborn babies to potential skeletal abnormalities.Molecular Psychiatry advance online publication, 8 September 2015; doi:10.1038/mp.2015.135.

Rapid effects of essential fatty acid deficiency on growth and development parameters and transcription of key fatty acid metabolism genes in juvenile barramundi (Lates calcarifer)

Barramundi (Lates calcarifer), a catadromous teleost of significant and growing commercial importance, are reported to have limited fatty acid bioconversion capability and therefore require preformed long-chain PUFA (LC-PUFA) as dietary essential fatty acid (EFA). In this study, the response of juvenile barramundi (47·0 g/fish initial weight) fed isolipidic and isoenergetic diets with 8·2 % added oil was tested. The experimental test diets were either devoid of fish oil (FO), and thus with no n-3 LC-PUFA (FO FREE diet), or with a low inclusion of FO (FO LOW diet). These were compared against a control diet containing only FO (FO CTRL diet) as the added lipid source, over an 8-week period. Interim samples and measurements were taken fortnightly during the trial in order to define the aetiology of the onset and progression of EFA deficiency. After 2 weeks, the fish fed the FO FREE and FO LOW diets had significantly lower live-weights, and after 8 weeks significant differences were detected for all performance parameters. The fish fed the FO FREE diet also had a significantly higher incidence of external abnormalities. The transcription of several genes involved in fatty acid metabolism was affected after 2 weeks of feeding, showing a rapid nutritional regulation. This experiment documents the aetiology of the onset and the progression of EFA deficiency in juvenile barramundi and demonstrates that such deficiencies can be detected within 2 weeks in juvenile fish.

Transcranial magnetic stimulation in autism spectrum disorder: challenges, promise, and roadmap for future research

Autism Spectrum Disorder (ASD) is a behaviorally defined complex neurodevelopmental syndrome characterized by impairments in social communication, by the presence of restricted and repetitive behaviors, interests and activities, and by abnormalities in sensory reactivity. Transcranial magnetic stimulation (TMS) is a promising, emerging tool for the study and potential treatment of ASD. Recent studies suggest that TMS measures provide rapid and noninvasive pathophysiological ASD biomarkers. Furthermore, repetitive TMS (rTMS) may represent a novel treatment strategy for reducing some of the core and associated ASD symptoms. However, the available literature on the TMS use in ASD is preliminary, composed of studies with methodological limitations. Thus, off-label clinical rTMS use for therapeutic interventions in ASD without an investigational device exemption and outside of an IRB approved research trial is premature pending further, adequately powered and controlled trials. Leaders in this field have gathered annually for a two-day conference (prior to the 2014 and 2015 International Meeting for Autism Research, IMFAR) to share recent progress, promote collaboration across laboratories, and establish consensus on protocols. Here we review the literature in the use of TMS in ASD in the context of the unique challenges required for the study and exploration of treatment strategies in this population. We also suggest future directions for this field of investigations. While its true potential in ASD has yet to be delineated, TMS represents an innovative research tool and a novel, possibly transformative approach to the treatment of neurodevelopmental disorders. Autism Res 2015. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Relative toxicity of selective serotonin reuptake inhibitors (SSRIs) in overdose

BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) have increasingly replaced tricyclic antidepressants (TCAs) in the treatment of depression. They appear to be safer in overdose, but there is little information on their spectrum of toxicity in overdose, or relative toxicity of each agent. OBJECTIVE: To determine the effect of SSRIs in overdose, as a group, and the relative toxicity of five different SSRIs. METHODS: A review of consecutive SSRI poisoning admissions to a single toxicology unit. Outcomes examined were length of stay [LOS], intensive care [ICU] admission rate, coma, seizures, electrocardiographic [ECG] abnormalities, and presence of serotonin syndrome [SS]. Logistic regression was used to model the outcome QTc >440 msec. RESULTS: There were 469 SSRI poisoning admissions analyzed after exclusions. The median LOS for all SSRI overdose admissions was 15.3 h (IQR: 10.5-21.3) and 30 of 469 (6.4%; 95% CI 4.3-9.0%) cases were admitted to ICU. The incidence of seizures was 1.9% and coma was 2.4%. Serotonin syndrome occurred in 14% of overdoses. Comparison of median QTc intervals of the five SSRIs was significantly different (p=0.0002); citalopram (450 IQR: 436-484) was individually different to fluoxetine (p=0.045), fluvoxamine (p=0.022), paroxetine (p=0.0002), and sertraline (p=0.001). The proportion of citalopram overdoses with a QTc >440 msec was 68%, differing significantly from sertraline (adjusted OR: 5.11 95% CI 2.32-11.27). Comparison of median QT intervals of the five SSRIs was statistically different (p=0.026); citalopram (400 IQR: 380-440) was individually different from sertraline (p=0.023). CONCLUSIONS: This study shows SSRIs are relatively safe in overdose despite serotonin syndrome being common. The exception was citalopram, which was significantly associated with QTc prolongation. We believe that cardiac monitoring should be considered in citalopram overdose, particularly with large ingestions and patients with associated cardiac disease.

Visual impairment in Australia: distance visual acuity, near vision, and visual field findings of the Melbourne Visual Impairment Project

PURPOSE: To describe the age-specific and gender-specific rates of blindness and visual impairment in urban adults aged 40 years and older. METHODS: A population-based sample of residents was recruited. Presenting and best-corrected distance visual acuities were assessed. Functional near vision was measured at each participant's preferred distance. Visual field examination was performed with a Humphrey Field Analyzer (HFA); those unable to perform the field analyzer test attempted a Bjerrum screen or confrontation field. RESULTS: The study population comprised 3,271 residents (83% of eligible) from ages 40 to 98 years; 54% were women. Overall, 56% of the study population wore distance correction; this was significantly lower in men but higher in the older age groups. Age-adjusted rates of blindness were 0.066% in men and 0.170% in women. Vision with current correction improved after refraction by gender and age. Direct age-standardized rates of functional near vision did not vary significantly by gender. Forty-six people had significant visual field loss in their better eye. The proportion of participants with constriction of the visual field to within 20 degrees of fixation was similar for men and women when controlled for age (odds ratio, 0.81; 95% confidence interval, 0.44 to 1.49) but increased significantly with age controlled for gender. Visual field abnormalities were detected in 548 right eyes (17%) and 533 left eyes (16%). CONCLUSIONS: Although overall rates of blindness because of visual acuity loss were relatively low, nearly three times more people had visual impairment because of visual field loss than visual acuity loss. These results highlight the need to target blindness prevention programs to the aging population, with a special emphasis on women.

The adaptable buffer algorithm for high quantile estimation in non-stationary data streams

The need to estimate a particular quantile of a distribution is an important problem which frequently arises in many computer vision and signal processing applications. For example, our work was motivated by the requirements of many semi-automatic surveillance analytics systems which detect abnormalities in close-circuit television (CCTV) footage using statistical models of low-level motion features. In this paper we specifically address the problem of estimating the running quantile of a data stream with non-stationary stochasticity when the memory for storing observations is limited. We make several major contributions: (i) we derive an important theoretical result which shows that the change in the quantile of a stream is constrained regardless of the stochastic properties of data, (ii) we describe a set of high-level design goals for an effective estimation algorithm that emerge as a consequence of our theoretical findings, (iii) we introduce a novel algorithm which implements the aforementioned design goals by retaining a sample of data values in a manner adaptive to changes in the distribution of data and progressively narrowing down its focus in the periods of quasi-stationary stochasticity, and (iv) we present a comprehensive evaluation of the proposed algorithm and compare it with the existing methods in the literature on both synthetic data sets and three large 'real-world' streams acquired in the course of operation of an existing commercial surveillance system. Our findings convincingly demonstrate that the proposed method is highly successful and vastly outperforms the existing alternatives, especially when the target quantile is high valued and the available buffer capacity severely limited.

Two maximum entropy-based algorithms for running quantile estimation in nonstationary data streams

The need to estimate a particular quantile of a distribution is an important problem that frequently arises in many computer vision and signal processing applications. For example, our work was motivated by the requirements of many semiautomatic surveillance analytics systems that detect abnormalities in close-circuit television footage using statistical models of low-level motion features. In this paper, we specifically address the problem of estimating the running quantile of a data stream when the memory for storing observations is limited. We make the following several major contributions: 1) we highlight the limitations of approaches previously described in the literature that make them unsuitable for nonstationary streams; 2) we describe a novel principle for the utilization of the available storage space; 3) we introduce two novel algorithms that exploit the proposed principle in different ways; and 4) we present a comprehensive evaluation and analysis of the proposed algorithms and the existing methods in the literature on both synthetic data sets and three large real-world streams acquired in the course of operation of an existing commercial surveillance system. Our findings convincingly demonstrate that both of the proposed methods are highly successful and vastly outperform the existing alternatives. We show that the better of the two algorithms (data-aligned histogram) exhibits far superior performance in comparison with the previously described methods, achieving more than 10 times lower estimate errors on real-world data, even when its available working memory is an order of magnitude smaller.

Histological, growth and 7-ethoxyresorufin 0-deethylase (EROD) activity responses of greenback flounder Rhombosolea tapirina to contaminated marine sediment and diet

Pathological abnormalities and mixed function oxygenase (MFO) enzyme changes are frequently used as indicators of anthropogenic contaminant exposure and effect. However, there is a paucity of research investigating the effects of contaminated sediment on native Australian benthic teleosts. As part of an ecotoxicological assessment of contaminated marine sediments in northern Tasmania, CYP1A induction, histological and growth response of the greenback flounder, Rhombosolea tapirina, exposed to contaminated marine sediments were examined. Hatchery reared flounder were exposed to reference sediment, contaminated sediment or contaminated sediment and diet for 6 weeks. CYP1A induction, using the ethoxyresorufin-O-deethylase (EROD) assay, and the histological and growth response in the flounder were examined on cessation of the exposure trial. Significant differences were found between treatments in histological, growth and EROD response. Exposure to contaminated sediment and diet elicited a multi-organ histological response: principally partial and total epidermal erosion and multifocal necrosis of the liver. The prevalence of total epidermal erosion was greatest with exposure to disturbed contaminated sediment (66.65±16.65%). The prevalence of multifocal necrosis of the liver was greatest with exposure to contaminanted sediment and diet (66.65±16.65%). Growth reduction, measured as percentage growth inhibition, was evident in flounder exposed to contaminated sediment and diet (18.2±11.99%). Additionally, exposure to contaminated sediment and diet elicited elevated induction of the EROD liver detoxification enzyme (139.65±24.22 pmol/min/mg protein) compared to exposure to contaminated sediment and non-contaminated diet (6.25±0.81 pmol/min/mg) indicating the presence and potential bioavailability of xenobiotics via food. Further, more inhibited growth and histological alteration associated with exposure to contaminated sediment and diet suggest contaminants in Deceitful Cove sediment are cytotoxic.

Effective and efficient detection of premature ventricular contractions based on variation of principal directions

Classification of electrocardiogram (ECG) data stream is essential to diagnosis of critical heart conditions. It is vital to accurately detect abnormality in the ECG in order to prevent possible beginning of life-threatening cardiac symptoms. In this paper, we focus on identifying premature ventricular contraction (PVC) which is one of the most common heart rhythm abnormalities. We use "Replacing" strategy to check the effects of each individual heartbeat on the variation of principal directions. Based on this idea, an online PVC detection method is proposed to classify the new arriving PVC beats in the real-time and online manner. The proposed approach is tested on the MIT-BIH arrhythmia database (MIT-BIH-AR). The PVC detection accuracy was 98.77%, with the sensitivity and positive predictivity of 96.12% and 86.48%, respectively. These results are an improvement on previous reported results for PVC detection. In addition, our proposed method is effective in terms of computation time. The average execution time of our proposed method was 3.83 s for a 30 min ECG recording. It shows the capability of the classifier to detect abnormal PVCs in online manner.