The 2-deoxyglucose uptake method as a first screen for neurotoxic compounds

1984 ◽  
Vol 62 (8) ◽  
pp. 998-1009 ◽  
Author(s):  
P. Muller ◽  
Lise Martin

Our primary goal is to develop a screening procedure to detect and partially characterize neurotoxic compounds. There is a great need for a new approach to screening for neurotoxicants because our industrialized world abounds with untested and potentially neurotoxic compounds. A large number of new compounds are introduced each year. Although a number of testing approaches to the screening for neurotoxicants have been proposed in the recent years, a consensus on the most adequate approach is yet to emerge. The existing methods share a number of shortcomings. Thus, most methods only detect a fraction of the tested neurotoxicants. Other methods lack the necessary resolution to detect the neurotoxic damage reproducibly and reliably. Furthermore, many screening approaches are too time consuming and costly to be used for the large-scale screening of neurotoxicants. It is, therefore, imperative to develop reliable and efficient screening methods applicable in regulatory toxicology. In this report, we describe two versions of the same method that we feel may be very beneficial for the large-scale screening of neurotoxicants. The 2-deoxyglucose (2-DG) uptake method provides an indirect measure of neuronal activity in different areas of the brain. The ability of the method to detect most, if not all, neuroactive substances is reviewed in this report. In the context of this report, a neuroactive substance is defined as a substance acting directly on the central or peripheral nervous system neurons and (or) glia. The 2-DG method equals the sensitivity of the most sensitive alternative methods which were selectively designed to detect the effects of specific groups of compounds. The generality and sensitivity of the 2-DG method are of major importance. Thus, if a tested compound does not affect the uptake of 2-DG into the brain, it is not likely to be neuroactive. Since neurotoxic compounds are a subset of neuroactive compounds, a compound that is not neuroactive is also not neurotoxic. Thus, a single test may, in some instances, determine if a tested compound is nontoxic. In addition, it appears that each compound or, at least, each family of compounds produces a characteristic profile ("pattern") of the sites of altered 2-DG uptake. This pattern can be exploited to characterize the tested compound and help us decide whether it is neurotoxic or neuroactive. Preliminary results from our laboratory indicate classical neurotoxic agents such as acrylamide, triethyltin, and 2,5-hexanedione induce a generalized depression of the 2-DG uptake throughout the brain. As a result, it may be difficult to differentiate these compounds on the basis of their respective 2-DG pattern. On the other hand, most of the therapeutics tested to date have distinct 2-DG uptake patterns which may help to distinguish therapeutics from classicial neurotoxicants. Additional experimental work is required to clarify this matter. The method has not been extensively used in the field of toxicology, mainly because the existing original 2-DG method is too complex and expensive for the large-scale screening for neurotoxicants. In this report, we review the efforts made to simplify this method as a general neurotoxicology screen. Our initial experience with this method in testing for neurotoxic compounds is also reviewed.

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii215-ii216
Author(s):  
Renee Hirte ◽  
Ian E Olson ◽  
Masum Rahman ◽  
Moustafa Mansour ◽  
Amanda Munoz Casabella ◽  
...  

Abstract Glioblastoma multiforme (GBM) is the most aggressive CNS neoplasm with a mere 15 month progression-free survival following current standards-of-care. Furthermore, conventional therapies have been effective, in part, by inducing a senescent-like phenotype in at least a proportion of glioma, as well as within the tumor-adjacent, healthy brain cells. Through an N-glyco-capture large-scale screening method, we were able to identify 25 genes exclusively overexpressed on glioma cell surfaces. Of those 25 targets, CD38 was an attractive target due to pre-existing FDA approved therapeutics. Recent studies have shown, however, that senescent cells, such as those induced via chemo- and radiotherapies, secrete a pro-inflammatory array of cytokines, known collectively as senescence associated secretory phenotype (SASP), that are capable of increasing CD38 expression in monocytes. CD38 functions as an ectoenzyme to convert extracellular NAD+ to nicotinamide (required for glioma cell salvage pathway NAD+ synthesis) and ADPR/cADPR (a cellular proliferation signal). To examine the effects of radiation on human glioma tissue, we performed reverse cyclase assays (RCA) on paired primary and recurrent human glioma tissue samples and found an increase in CD38 activity in post-irradiated tissues (recurrent glioma) compared to pre-irradiated (primary glioma). Through proliferation assays, we also found an increase in glioma cell growth following treatment with cADPR compared to untreated. Our results demonstrate that CD38 activity is tumorgenic, and furthermore that conventional chemo- and radiotherapies increase this CD38 activity. This indicates that treating CD38 with previously FDA approved therapeutics may provide hope for increasing progression free survival in our GBM patient population, and moreover emphasize the importance of leveraging novel large scale screening methods for identifying additional opportunities for treatment.


2017 ◽  
Vol 61 (5) ◽  
Author(s):  
Nuno Vale ◽  
Maria João Gouveia ◽  
Gabriel Rinaldi ◽  
Paul J. Brindley ◽  
Fátima Gärtner ◽  
...  

ABSTRACT Schistosomiasis, a major neglected tropical disease, affects more than 250 million people worldwide. Treatment of schistosomiasis has relied on the anthelmintic drug praziquantel (PZQ) for more than a generation. PZQ is the drug of choice for the treatment of schistosomiasis; it is effective against all major forms of schistosomiasis, although it is less active against juvenile than mature parasites. A pyrazino-isoquinoline derivative, PZQ is not considered to be toxic and generally causes few or transient, mild side effects. Increasingly, mass drug administration targeting populations in sub-Saharan Africa where schistosomiasis is endemic has led to the appearance of reduced efficacy of PZQ, which portends the selection of drug-resistant forms of these pathogens. The synthesis of improved derivatives of PZQ is attracting attention, e.g., in the (i) synthesis of drug analogues, (ii) rational design of pharmacophores, and (iii) discovery of new compounds from large-scale screening programs. This article reviews reports from the 1970s to the present on the metabolism and mechanism of action of PZQ and its derivatives against schistosomes.


Genes ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1452
Author(s):  
Audrey Defosset ◽  
Dorine Merlat ◽  
Laetitia Poidevin ◽  
Yannis Nevers ◽  
Arnaud Kress ◽  
...  

Multiciliogenesis is a complex process that allows the generation of hundreds of motile cilia on the surface of specialized cells, to create fluid flow across epithelial surfaces. Dysfunction of human multiciliated cells is associated with diseases of the brain, airway and reproductive tracts. Despite recent efforts to characterize the transcriptional events responsible for the differentiation of multiciliated cells, a lot of actors remain to be identified. In this work, we capitalize on the ever-growing quantity of high-throughput data to search for new candidate genes involved in multiciliation. After performing a large-scale screening using 10 transcriptomics datasets dedicated to multiciliation, we established a specific evolutionary signature involving Otomorpha fish to use as a criterion to select the most likely targets. Combining both approaches highlighted a list of 114 potential multiciliated candidates. We characterized these genes first by generating protein interaction networks, which showed various clusters of ciliated and multiciliated genes, and then by computing phylogenetic profiles. In the end, we selected 11 poorly characterized genes that seem like particularly promising multiciliated candidates. By combining functional and comparative genomics methods, we developed a novel type of approach to study biological processes and identify new promising candidates linked to that process.


1976 ◽  
Vol 7 (4) ◽  
pp. 236-241 ◽  
Author(s):  
Marisue Pickering ◽  
William R. Dopheide

This report deals with an effort to begin the process of effectively identifying children in rural areas with speech and language problems using existing school personnel. A two-day competency-based workshop for the purpose of training aides to conduct a large-scale screening of speech and language problems in elementary-school-age children is described. Training strategies, implementation, and evaluation procedures are discussed.


2019 ◽  
Author(s):  
Ryther Anderson ◽  
Achay Biong ◽  
Diego Gómez-Gualdrón

<div>Tailoring the structure and chemistry of metal-organic frameworks (MOFs) enables the manipulation of their adsorption properties to suit specific energy and environmental applications. As there are millions of possible MOFs (with tens of thousands already synthesized), molecular simulation, such as grand canonical Monte Carlo (GCMC), has frequently been used to rapidly evaluate the adsorption performance of a large set of MOFs. This allows subsequent experiments to focus only on a small subset of the most promising MOFs. In many instances, however, even molecular simulation becomes prohibitively time consuming, underscoring the need for alternative screening methods, such as machine learning, to precede molecular simulation efforts. In this study, as a proof of concept, we trained a neural network as the first example of a machine learning model capable of predicting full adsorption isotherms of different molecules not included in the training of the model. To achieve this, we trained our neural network only on alchemical species, represented only by their geometry and force field parameters, and used this neural network to predict the loadings of real adsorbates. We focused on predicting room temperature adsorption of small (one- and two-atom) molecules relevant to chemical separations. Namely, argon, krypton, xenon, methane, ethane, and nitrogen. However, we also observed surprisingly promising predictions for more complex molecules, whose properties are outside the range spanned by the alchemical adsorbates. Prediction accuracies suitable for large-scale screening were achieved using simple MOF (e.g. geometric properties and chemical moieties), and adsorbate (e.g. forcefield parameters and geometry) descriptors. Our results illustrate a new philosophy of training that opens the path towards development of machine learning models that can predict the adsorption loading of any new adsorbate at any new operating conditions in any new MOF.</div>


2019 ◽  
Vol 19 (1) ◽  
pp. 4-16 ◽  
Author(s):  
Qihui Wu ◽  
Hanzhong Ke ◽  
Dongli Li ◽  
Qi Wang ◽  
Jiansong Fang ◽  
...  

Over the past decades, peptide as a therapeutic candidate has received increasing attention in drug discovery, especially for antimicrobial peptides (AMPs), anticancer peptides (ACPs) and antiinflammatory peptides (AIPs). It is considered that the peptides can regulate various complex diseases which are previously untouchable. In recent years, the critical problem of antimicrobial resistance drives the pharmaceutical industry to look for new therapeutic agents. Compared to organic small drugs, peptide- based therapy exhibits high specificity and minimal toxicity. Thus, peptides are widely recruited in the design and discovery of new potent drugs. Currently, large-scale screening of peptide activity with traditional approaches is costly, time-consuming and labor-intensive. Hence, in silico methods, mainly machine learning approaches, for their accuracy and effectiveness, have been introduced to predict the peptide activity. In this review, we document the recent progress in machine learning-based prediction of peptides which will be of great benefit to the discovery of potential active AMPs, ACPs and AIPs.


2018 ◽  
Vol 18 (4) ◽  
pp. 300-311
Author(s):  
Ana Claudia Torrecilhas ◽  
Patricia Xander ◽  
Karen Spadari Ferreira ◽  
Wagner Luiz Batista

The neglected tropical diseases (NTDs) are caused by several parasites, fungi, bacteria and viruses and affect more than one billion people in the world. The control and prevention against NTDs need implementation of alternative methods for testing new compounds against these diseases. For the implementation of alternative methods, it is necessary to apply the principles of replacement, reduction and refinement (the 3Rs) for the use of laboratory animals. Accordingly, the present review addressed a variety of alternative models to study the infections caused by protozoa and fungi. Overall, vertebrate and invertebrate models of fungal infection have been used to elucidate host-pathogen interactions. However, until now the insect model has not been used in protozoal studies as an alternative method, but there is interest in the scientific community to try new tools to screen alternative drugs to control and prevent protozoal infections.


Author(s):  
Stefano Vassanelli

Establishing direct communication with the brain through physical interfaces is a fundamental strategy to investigate brain function. Starting with the patch-clamp technique in the seventies, neuroscience has moved from detailed characterization of ionic channels to the analysis of single neurons and, more recently, microcircuits in brain neuronal networks. Development of new biohybrid probes with electrodes for recording and stimulating neurons in the living animal is a natural consequence of this trend. The recent introduction of optogenetic stimulation and advanced high-resolution large-scale electrical recording approaches demonstrates this need. Brain implants for real-time neurophysiology are also opening new avenues for neuroprosthetics to restore brain function after injury or in neurological disorders. This chapter provides an overview on existing and emergent neurophysiology technologies with particular focus on those intended to interface neuronal microcircuits in vivo. Chemical, electrical, and optogenetic-based interfaces are presented, with an analysis of advantages and disadvantages of the different technical approaches.


Author(s):  
Hugues Duffau

Investigating the neural and physiological basis of language is one of the most important challenges in neurosciences. Direct electrical stimulation (DES), usually performed in awake patients during surgery for cerebral lesions, is a reliable tool for detecting both cortical and subcortical (white matter and deep grey nuclei) regions crucial for cognitive functions, especially language. DES transiently interacts locally with a small cortical or axonal site, but also nonlocally, as the focal perturbation will disrupt the entire subnetwork sustaining a given function. Thus, in contrast to functional neuroimaging, DES represents a unique opportunity to identify with great accuracy and reproducibility, in vivo in humans, the structures that are actually indispensable to the function, by inducing a transient virtual lesion based on the inhibition of a subcircuit lasting a few seconds. Currently, this is the sole technique that is able to directly investigate the functional role of white matter tracts in humans. Thus, combining transient disturbances elicited by DES with the anatomical data provided by pre- and postoperative MRI enables to achieve reliable anatomo-functional correlations, supporting a network organization of the brain, and leading to the reappraisal of models of language representation. Finally, combining serial peri-operative functional neuroimaging and online intraoperative DES allows the study of mechanisms underlying neuroplasticity. This chapter critically reviews the basic principles of DES, its advantages and limitations, and what DES can reveal about the neural foundations of language, that is, the large-scale distribution of language areas in the brain, their connectivity, and their ability to reorganize.


Author(s):  
Pooja Prabhu ◽  
A. K. Karunakar ◽  
Sanjib Sinha ◽  
N. Mariyappa ◽  
G. K. Bhargava ◽  
...  

AbstractIn a general scenario, the brain images acquired from magnetic resonance imaging (MRI) may experience tilt, distorting brain MR images. The tilt experienced by the brain MR images may result in misalignment during image registration for medical applications. Manually correcting (or estimating) the tilt on a large scale is time-consuming, expensive, and needs brain anatomy expertise. Thus, there is a need for an automatic way of performing tilt correction in three orthogonal directions (X, Y, Z). The proposed work aims to correct the tilt automatically by measuring the pitch angle, yaw angle, and roll angle in X-axis, Z-axis, and Y-axis, respectively. For correction of the tilt around the Z-axis (pointing to the superior direction), image processing techniques, principal component analysis, and similarity measures are used. Also, for correction of the tilt around the X-axis (pointing to the right direction), morphological operations, and tilt correction around the Y-axis (pointing to the anterior direction), orthogonal regression is used. The proposed approach was applied to adjust the tilt observed in the T1- and T2-weighted MR images. The simulation study with the proposed algorithm yielded an error of 0.40 ± 0.09°, and it outperformed the other existing studies. The tilt angle (in degrees) obtained is ranged from 6.2 ± 3.94, 2.35 ± 2.61, and 5 ± 4.36 in X-, Z-, and Y-directions, respectively, by using the proposed algorithm. The proposed work corrects the tilt more accurately and robustly when compared with existing studies.


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