Glutamatergic hyperfunctioning during alcohol withdrawal syndrome: Therapeutic perspective with zinc and magnesium

It is known that the glutamatergic pathways are hyperfunctioning during alcohol withdrawal syndrome. It has been demonstrated that hyperfunctioning of this system causes a great damage to the superior cortical activity, the ability to concentrate and the control of impulses. Recent studies show that the cations zinc and magnesium modulate the glutamatergic function, reducing it to non-toxic levels, yet not reducing it to the point of depriving this neurotransmitter of its normal activity. New perspectives of treatment focus on the modulation of this system, having, as a result, reestablishment of impulse control abilities, damage prevention to the hippocampus and the amygdala and prevention of future relapses. (C) 2011 Elsevier B.V. All rights reserved.Universidade Federal de São Paulo, Dept Psychobiol, BR-04024002 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Med, BR-04024002 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Psychobiol, BR-04024002 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Med, BR-04024002 São Paulo, BrazilWeb of Scienc

Influence of Microelement Concentration on the Intensity of Alcohol Withdrawal Syndrome

Aims: To establish a nutritional and constitutional profile concerning the micronutrient plasma concentration of patients who suffer from AWS. Method: Observational case control study to determine whether patients who exhibited symptoms of AWS (N = 60) had micronutrient plasmatic concentration deficiencies when compared with healthy controls (N = 34). Results: There were statistically significant differences between the concentrations of nutrients that are correlated with glutamate hyperactivity (zinc, magnesium and folate/vitamin B12/homocysteine). Conclusion: Evidence from literature and our experiment suggests that brain activity, especially the glutamatergic system, might be directly involved in micronutrient concentrations. Therefore, their supplementation to the AWS patient might improve symptom evolution.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Associacao Fundo de Incentivo a Pesquisa (AFIP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Federal de São Paulo UNIFESP, Dept Psychobiol, São Paulo, BrazilCtr Referencia Tratamento Alcool Tabaco & Outras, São Paulo, BrazilUniversidade Federal de São Paulo UNIFESP, Dept Psychobiol, São Paulo, BrazilFAPESP: 2012/06731-4Web of Scienc

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects

Abstract Artificial intelligence (AI) is transforming the field of medical imaging and has the potential to bring medicine from the era of ‘sick-care’ to the era of healthcare and prevention. The development of AI requires access to large, complete, and harmonized real-world datasets, representative of the population, and disease diversity. However, to date, efforts are fragmented, based on single–institution, size-limited, and annotation-limited datasets. Available public datasets (e.g., The Cancer Imaging Archive, TCIA, USA) are limited in scope, making model generalizability really difficult. In this direction, five European Union projects are currently working on the development of big data infrastructures that will enable European, ethically and General Data Protection Regulation-compliant, quality-controlled, cancer-related, medical imaging platforms, in which both large-scale data and AI algorithms will coexist. The vision is to create sustainable AI cloud-based platforms for the development, implementation, verification, and validation of trustable, usable, and reliable AI models for addressing specific unmet needs regarding cancer care provision. In this paper, we present an overview of the development efforts highlighting challenges and approaches selected providing valuable feedback to future attempts in the area. Key points • Artificial intelligence models for health imaging require access to large amounts of harmonized imaging data and metadata. • Main infrastructures adopted either collect centrally anonymized data or enable access to pseudonymized distributed data. • Developing a common data model for storing all relevant information is a challenge. • Trust of data providers in data sharing initiatives is essential. • An online European Union meta-tool-repository is a necessity minimizing effort duplication for the various projects in the area